The Politics Of Public Accountability: Policy Design In Latin American Oil Exporting Countries 303028994X, 9783030289942, 9783030289959

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The Politics Of Public Accountability: Policy Design In Latin American Oil Exporting Countries
 303028994X,  9783030289942,  9783030289959

Table of contents :
Acknowledgements......Page 7
Contents......Page 8
About the Authors......Page 9
List of Figures......Page 10
List of Tables......Page 11
1 Research Problem......Page 12
2 General Aims......Page 15
3 Literature Review......Page 17
4 Research Method......Page 20
5 Book Organization......Page 23
References......Page 24
1 Introduction: The Shift to Policy Design......Page 30
2.1 A Typology of Policy Design Approaches......Page 32
2.2 Methodological Implications for Policy Design......Page 34
2.3 Four Models of Causation, Intervention, Evaluation and Instrumentation......Page 37
3.1 Policy Design as Emancipation......Page 39
3.2 Policy Design as Framing......Page 43
3.3 Policy Design as Instrumentation......Page 47
3.4 Policy Design as Institutionalization......Page 50
4 Conclusion: Comparative Policy Design......Page 54
References......Page 55
1 Introduction: Aligning Our Methods With Realism......Page 62
2.1 Causality as Necessity......Page 64
2.2 Causal Mechanisms as Causal Forces......Page 68
2.3 Case Selection for Small-n Comparison......Page 71
3.1 A Set-Theoretic Research Design......Page 74
3.2 Policy Instruments as Expected Empirical Observations......Page 75
3.3 Assessing Evidence With Bayesian Statistics......Page 78
3.4 Cross-case Comparison......Page 83
3.5 Research Protocol......Page 85
4.1.1 First Hypothesis: H1 = RN:PA−......Page 87
4.1.2 Coping With Context: H2 = RN∗¬Tr:PA−......Page 91
4.1.3 Empirical Tests Design......Page 93
4.2.1 Overall Cases Population......Page 95
4.2.2 Assessing Resource Nationalism......Page 96
4.2.3 Assessing Transparency Policies......Page 97
4.2.4 Assessing a Public Accountability Deficit......Page 98
4.3.1 Assessing Class Membership for the Trigger (T)......Page 99
4.3.3 Typology and Final Decision......Page 101
5 Conclusion: Synthesis......Page 102
References......Page 104
1 Introduction: The Political Economy of Resource Nationalism......Page 110
2 The Determinants of Oil Governance......Page 112
2.1.1 The Primary Exporter Model......Page 113
2.1.2 The Industrialization by Imports Substitution Model......Page 114
2.1.3 The Neoliberal Model......Page 115
2.1.4 The Nationalist Model......Page 116
2.2.1 The Historical Role of National Oil Companies......Page 117
2.2.2 Oil Policy Change and Path Dependence......Page 118
2.2.3 The Laws of FDI Attraction......Page 119
3.1 The Venezuelan Disease......Page 121
3.2 The Ecuadorian Riddle......Page 123
4.1 The Paradigm Shift in Mexico......Page 128
4.2 The Brazilian Paradox......Page 132
5 Conclusion: Empirical Findings......Page 138
References......Page 140
1 Introduction: The Infernal Spiral......Page 144
2.1 The Government’s Program: The Revival of the Great Colombia......Page 147
2.2 The Constitutive Regulation: The Constituent Assembly Takes Power......Page 148
2.3 The Development Model: The Bolivarian Alternative Agenda......Page 149
2.4 The State Apparatus Design: A New Geometry of Power......Page 150
3.1 Sectorial Planning: The “Oil Sovereignty Plan”......Page 151
3.2 Sectorial Regulation: PdVSA Harnesses the Oil Nationalization......Page 153
3.3 Sectorial Budget Allocation: Where Is the Money?......Page 154
3.4 Sectorial Organization: The Bureaucratic Centralization......Page 155
4.1 Cross-sectorial Planning: Information Is Power......Page 157
4.2 Cross-Sectorial Regulation: The Strategy of Authoritarian Legalism......Page 158
4.3 Cross-Sectorial Budget Allocation: When Centralism Meets With Discretion......Page 160
4.4 Cross-Sectorial Administration: Interventionist Planning and Neo-corporativism......Page 162
5.1 The Government’s Statements: Meritocracy Is a Myth......Page 163
5.2 The Legislative Process: The Institutionalization of Authoritarian Legalism......Page 165
5.3 Budget Elaboration: Manipulating Oil Rents for Social Control......Page 166
5.4 Local Governments in the Oil Policy: The Politics of Patronage......Page 167
6.1 Access to Information: The Legalization of Secrecy......Page 168
6.2 Due Process: A Judicial System Under Influence......Page 170
6.3 Financial Assessments: A Lack of Transparency and Timely Information......Page 172
6.4 Balance and Control Agencies: The Realm of Nepotism and Cronyism......Page 173
7 Conclusion: Synthesis......Page 175
References......Page 177
1.1 From the Resource Curse Thesis to Policy Design......Page 182
1.2 A Realist Approach to Policy Design......Page 183
1.3 A Causal Mechanism of Public Accountability Deficit......Page 185
2.1 Agenda Setting......Page 186
2.2 Policy Formulation......Page 187
2.3 Cross-Sectorial Coordination......Page 188
2.4 Political Interplays......Page 189
2.5 Policy Outcome......Page 190
3 Further Research......Page 191
References......Page 192
Appendix A: Assessing Causal Homogeneity......Page 193
Appendix B: Collected Evidence From the Venezuelan Case......Page 196
References......Page 212
Index......Page 234

Citation preview

INTERNATIONAL SERIES ON PUBLIC POLICY

The Politics of Public Accountability Policy Design in Latin American Oil Exporting Countries

Guillaume Fontaine Cecilia Medrano Caviedes Iván Narváez

International Series on Public Policy Series Editors B. Guy Peters Department of Political Science University of Pittsburgh Pittsburgh, PA, USA Philippe Zittoun Research Professor of Political Science LET-ENTPE, University of Lyon Lyon, France

The International Series on Public Policy - the official series of International Public Policy Association, which organizes the International Conference on Public Policy  - identifies major contributions to the field of public policy, dealing with analytical and substantive policy and governance issues across a variety of academic disciplines. A comparative and interdisciplinary venture, it examines questions of policy process and analysis, policymaking and implementation, policy instruments, policy change & reforms, politics and policy, encompassing a range of approaches, theoretical, methodological, and/or empirical. Relevant across the various fields of political science, sociology, anthropology, geography, history, and economics, this cutting edge series welcomes contributions from academics from across disciplines and career stages, and constitutes a unique resource for public policy scholars and those teaching public policy worldwide. All books in the series are subject to Palgrave’s rigorous peer review process: https://www.palgrave.com/gb/demystifying-peer-review/792492 More information about this series at http://www.palgrave.com/gp/series/15096

Guillaume Fontaine  Cecilia Medrano Caviedes • Iván Narváez

The Politics of Public Accountability Policy Design in Latin American Oil Exporting Countries

Guillaume Fontaine Latin American Faculty for Social Sciences Quito, Ecuador

Cecilia Medrano Caviedes Center for International Studies Paris, France

Iván Narváez Latin American Faculty for Social Sciences Quito, Ecuador

ISSN 2524-7301     ISSN 2524-731X (electronic) International Series on Public Policy ISBN 978-3-030-28994-2    ISBN 978-3-030-28995-9 (eBook) https://doi.org/10.1007/978-3-030-28995-9 © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

The idea of design is to link together values, models of causation, and the choice of instrumentation so that better choices can be made (Linder and Peters 1987, 468)

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Acknowledgements

This book is a product of a two-year research funded by FLACSO Ecuador though the grant #IP973. We are particularly thankful to our institution for this support. During the fieldwork we also benefited from the logistical support of the Energy Program at El Colegio de Mexico and the Department of Political Science at the University of Sao Paulo. We would like to express our special thanks to Isabelle Rousseau, José Luis Mendez and Adrián Gurza for their collaboration. The preliminary results were presented during two meetings at the International Public Policy Association and during the monthly seminar held by the Comparative Policy Analysis Lab at FLACSO. We are extremely grateful to B. Guy Peters, Derek Beach and Mike Howlett for taking time to read our working papers and for making us accurate and inspiring suggestions. We also thank our students from the Lab for their relentless curiosity and their patience in testing our theories and methods on their own research, thereby providing us invaluable feedbacks to improve the policy design framework. Quito, May 20, 2019

Guillaume Fontaine Cecilia Medrano Caviedes Iván Narváez

vii

Contents

1 Public Accountability Deficits as a Policy Problem  1 2 The Policy Design Framework 19 3 A Realist Approach to Policy Design 51 4 Open and Closed Resource Nationalism 99 5 How Resource Nationalism Hinders Public Accountability133 6 From Policy to Institutional Design171 Appendix A: Assessing Causal Homogeneity183 Appendix B: Collected Evidence From the Venezuelan Case187 References203 Index225

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About the Authors

Guillaume  Fontaine  is a senior researcher at FLACSO Ecuador. He graduated from the University Paris 3 and Sciences-Po (Paris), where he specialized in comparative policy analysis. He coordinates the Public Accountability Project, a collective research about public accountability deficits in various Latin American countries. He has published extensively on social environmental conflicts and democratic governance in Latin America. Cecilia Medrano Caviedes  is an analytical economist with a multidisciplinary background. She graduated from Sciences-Po (Paris) and The London School of Economics, where she specialized in the political economy of natural resources and the governance of extractive industries. She has been a consultant for the Natural Resource Governance Institute, Ciudadanos por la Transparencia, the Venezuelan Ministry of Finance, and the UNESCO. Iván Narváez  is a senior researcher at FLACSO Ecuador. He graduated from the University Simon Bolivar (Quito), where he specialized in environmental law and comparative constitutionalism. He has been CEO of the Environmental Protection Unit at Petroecuador. He has published extensively about indigenous rights and environmental governance in the Amazon region.

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List of Figures

Fig. 2.1 A typology of policy design models 27 Fig. 2.2 The policy design as emancipation model. (Source: Adapted from Bobrow 2006, 84) 28 Fig. 2.3 The policy design as framing model. (Source: Adapted from Hoppe 2014, 7) 33 Fig. 2.4 The policy design as instrumentation model. (Source: Adapted from Howlett 2011, 56) 37 Fig. 2.5 The policy design as institutionalization model. (Source: Adapted from Linder and Peters 1987, 470) 40 Fig. 3.1 A causal mechanism in policy design. (Source: Elaborated by the authors)64 Fig. 3.2 Standard operating procedures for comparative policy design. (Source: Elaborated by the authors) 75 Fig. 3.3 A simple theoretical causal mechanism of resource nationalism hindering public accountability (H1) 77 Fig. 3.4 A twofold theoretical causal mechanism of resource nationalism hindering public accountability (H2) 81

xiii

List of Tables

Table 1.1 Table 1.2 Table 2.1 Table 2.2 Table 3.1 Table 3.2 Table 3.3 Table 3.4 Table 3.5 Table 3.6 Table 3.7 Table 3.8 Table 3.9 Table 4.1 Table 4.2 Table 5.1 Table 5.2

Policy content by aims and means 10 A taxonomy of oil policy instruments according to the State’s resources11 Four methodologies 23 Methodological implications of different ontologies for policy design24 A typology of cases for consistency 62 Expected empirical observations in a policy design process 66 A typology of conventional tests 68 Bayesian formalization of conventional tests 69 Bayesian formalization of 4 × 4 hoop tests series 71 Cross-case comparison of causal mechanisms 73 Expected empirical observations in a policy design process 83 cs-QCA for causal homogeneity 89 A typology of oil and gas producing countries in LAC 91 Oil reserves in selected countries 100 Macroeconomics of selected countries 101 Positions occupied by former military under President Chavez (1999–2013)163 Bayesian formalization of positive hoop tests 165

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CHAPTER 1

Public Accountability Deficits as a Policy Problem

1   Research Problem Oil and gas are economically and politically significant natural resources, which have been related to nationalism in Latin America and the Caribbean since the early twentieth century. Nationalism may resort to the nationalization of strategic sectors in various ways and degrees (Cf. Philip 1989). Bolivia, for instance once adopted a “patriotic nationalism” in 1937 with the expropriation of Standard Oil of New Jersey which was suspected of treason during the Chaco War, long before adopting a “populist nationalism” with the nationalization of Gulf Oil as a result of the social pressure, in 1969. Nationalism can also aim at different purposes, according to a government’s needs. In 1948 Venezuela’s Energy Minister, Juan Pablo Pérez Alfonso, invented a “third-world nationalism” against US and European big oil companies interests, through a fifty-fifty rent-sharing system for the State and private companies, which he would help replicate in 1960 with the other founding members of the OPEC (Iraq, Kuwait, Iran and Saudi Arabia). This “non-nationalizing nationalism” was substituted by the 1973 nationalization of carbon-fuel fossils, alike the Bolivian nationalism. Meanwhile, the Army had Ecuador join the OPEC and adopted a “modernist nationalism” inspired by the Brazilian military government, leading to nationalize Gulf Oil’s assets in 1973 before assigning a monopolistic control of the local market to the national oil corporation CEPE, and finally giving control of the CEPE-Texaco consortium to the © The Author(s) 2020 G. Fontaine et al., The Politics of Public Accountability, International Series on Public Policy, https://doi.org/10.1007/978-3-030-28995-9_1

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Ecuadorian state, in 1976. The most recent trend of what has been coined “resource nationalism” refers to “the maximization of public revenues; the assertion of strategic state control (ability to set political or strategic direction to the development of the sector); and enhancement of developmental spillovers from extractive activity” (Haslam and Heidrich 2016b, 1). This trend can be identified as a policy paradigm shift reverting the neoliberal cycle launched during the 1980s, in the aftermath of the Latin American debt crisis. The total population of Latin American oil and gas exporting countries includes Argentina, Bolivia, Brazil, Colombia, Ecuador, Mexico, Peru, Trinidad and Tobago and Venezuela. Among these, six countries have experienced resource nationalism at various degrees during the past two decades (namely Mexico, Brazil, Venezuela, Bolivia, Ecuador and Argentina) while the other three kept on implementing liberal policies (namely Colombia, Peru and Trinidad and Tobago). While most radical nationalism reached nationalization and expropriation—like in Bolivia, Venezuela, Ecuador and Argentina—moderate nationalism limited to further protection of the national company combined with controlled intervention of the private sector, like in Brazil and Mexico. Mineral endowment has contradictory effects on economic development and democracy. For instance, early works on Venezuela used to emphasize the negative effects of the rentier state on democratic institutions (Karl 1997; Ross 2001) but more recent studies have shown that oil rents might as well have supported democracy at least until the 1990 crisis (Dunning 2008; Ross 2012). This controversy underlies how much public policies and political institutions are key to explain the State’s capacity to cope with the effects of price shocks and rent booming, while attending social demands. In particular, social and political accountability are at the core of the discussion for they constitute the ultimate safeguards against patronage and corruption (Karl 2007). The determinant of resource nationalism is a government’s technical and financial needs, and their capacity to invest and develop the extractive sector in absence of foreign direct investments (FDI). The bottom line is the more a country depends on a single resource extraction, the more it controls FDI.  Things are slightly different in countries where access to strategic resources like oil is difficult, or when the resource endowment has created a dependence on a single source of rents. The initial stage is also key to explain further developments of resource nationalism, whether oil discoveries happen in a context of high or low prices, and can be

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exploited by existing national oil companies with high or low technical and financial capacities. On the one hand, the more a country has access to cheap oil (which can be measured in different ways, like the drilling success rate, production costs, proven reserves and tradable volume) or other minerals, the less a government needs to sacrifice a it’s sovereignty to attract FDI, the more it tends to radicalize resource nationalism. This would explain why Venezuela, Ecuador and Bolivia have been through less radical reforms than Brazil, and why Colombia and Mexico progressively opened their extractive sector to the private sector. On the other hand, since private investments require information and legal security, if a government wants to attract FDI they have to foster accountability, at least between the State and economic actors. But what about accountability by the State towards citizens? How is it affected by resource nationalism? Our argument is that resource nationalism hinders accountability at different levels when mineral prices are high. It affects vertical accountability because the incumbent benefits more than outsiders from those rents, which affects the laters’ chances to be elected. It also affects horizontal accountability since the executive concentrates power over the judicial and the legislative, which affects the effectiveness of balance agencies. It affects social accountability because the government controls information and social groups through dedicated agencies.1 On the hand, the degree to which resource nationalism affects accountability depends on the modalities of the implemented nationalist reforms. The three countries where the most radical reform have been implemented since the 2000s (namely Bolivia, Venezuela and Ecuador) registered the lowest scores and rank among the worst countries in Latin America of the Resource Governance Index (NRGI 2017).2 But the paradox is countries where a moderate resource nationalism has been implemented (Brazil and Mexico) register the highest scores and rank among the best countries in 1  Vertical accountability refers to electoral mechanisms of control by citizenship over the state, while horizontal accountability refers to the classic separation of the executive, the legislative and the judicial powers, while (O’Donnell 1999, 38). Social accountability is a vertical but non-electoral form of pressure to have civil servants and elected representatives justify and inform on their decisions, and possibly be sanctioned when acting in a wrong or illegal way (Peruzzotti and Smulovitz 2002). 2  The resource governance index is based on four indicators measuring institutional and legal setting, reporting practices, safeguards and quality controls, and enabling environment.

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the region. Between these extremes are countries where the extractive sector remains market-driven with a minimum degree of State intervention (Peru, Trinidad and Tobago, Colombia and Chile). In other words, the incidence of ideas on policy outcomes depends on institutional factors.

2   General Aims The ultimate goal of our research was to explain consistently the role of ideas and institutions in policy outcomes. We were seeking for a causal mechanism linking ideas and policy outcomes through institutional arrangements. In particular, we focused on policy design to describe the role of instruments selection and combination in improving or reducing social and political accountability. More specifically, drawing from the case of public accountability deficits in oil and gas exporting countries, we intended to shed light on the relation between resource nationalism and democracy. Ideas are arguably a catch-all concept, difficult to observe empirically and to measure, if not by narratives, discursive analysis and thick descriptions. In policy analysis, they are generally considered an “insufficient but necessary part of a condition which is itself unnecessary but sufficient for the result” (INUS) (emphasize is ours, see Mackie 1965). According to the context and the policy at stake, “ideational” factors are expected to shape policies as critical environmental variables or as motivations at both individual and collective levels (Berman 2013). A crude taxonomy of ideas distinguishes policy paradigms from programmatic ideas, frames and public sentiment (Campbell 1998, 385). Resource nationalism qualifies as a policy paradigm insofar as it refers to a cognitive framework where the State assumes a driving role in economic development, with the government defending a patriotic view of politics and diplomacy. Nationalism can be defined in many different ways, according to epistemological considerations. It can refer to the process of formation or development of nations, a feeling or the conscience of being part of a nation, the language and symbolism of a nation, a socio-political movement acting on behalf of a nation, a doctrine or an ideology of the nation (Smith 2010, 5–6). Ours is a socio-political definition of nationalism as a political regime where state-centered development policies are implemented under a hierarchical governance mode, by a government claiming legitimacy from the people to affirm their national sovereignty against globalization trends.

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Policy paradigms have enjoyed a particular attention by scholars interested in policy change for the past three decades, after Peter Hall’s pathbreaking study of the neo-liberal turn in Britain and France in the early 1980s (Hall 1986).3 They came after Thomas Kuhn’s theory of scientific revolution, which defined a paradigm as a series of outcomes universally acknowledged by a scientific community that provides them for a while with patterns of problems and solutions (Kuhn 2012). However, the conceptual stretching of policy paradigms raises a major objection to their utility for other than illustrative purpose. It also faces problems of circularity, since the alleged causal factor (a paradigm shift) acts as an outcome when it comes to describe the very nature of policy change. Some argue that it fails to explain causality between political ideas, institutions and policy change (Campbell 2002). Others contend that policy paradigm changes are not the product of exogenous factors (Cashore and Howlett 2007; Howlett and Migone 2011) or that the original “incommensurability principle” (Kuhn 2012) is inaccurate for policy analysis, since a paradigm shift can occur by drifting or layering (Daigneault 2014; Hogan and Howlett 2015). Explaining policy paradigm changes would then merely consist in a hermeneutics of the dispute about the interpretation of policy anomalies (Wilder and Howlett 2015). Drawing from Peter Hall’s three-order-change theory4 (Hall 1993, 279), we argue that a policy paradigm shift is a process by which ideas and institutions interplay and reinforce one another at three levels. At a normative level, ideas act as a trigger for a major change in the cognitive 3  Policy paradigms have been used to describe major changes in European economic policies (Campbell 1998; Hodson and Mabbett 2009) and the effects of neoliberalism brought out by the “Washington Consensus” in Latin America (Babb 2013). They have also been tested on a great deal of sectorial policies, including the French cultural policy (Surel 1997), the forest policy in Northwestern USA (Cashore and Howlett 2007) and the energetic transition towards renewable sources (Kern and Kuzemko 2014). They are referred to by scholars wondering if the 2008 sub-primes crisis in the US and the 2011 crisis in weak UE economies like Greece, Italy and Spain are signs of a new “paradigm shift” coming out, from neoliberalism to “post-neoliberalism” (sic) (Hall 2013; Béland and Cox 2013; Blyth 2013; Berman 2013; Daigneault 2014). 4  A third-order change refers to change in normative aims which act as a trigger for major changes in the general definition of means, such as constitutional and institutional systems reforms. A second-order change refers to strategic aims according to which policy design is made through an instrument mix. A first-order change refers to operational aims guiding these instruments calibration at an early stage of policy implementation and following a learning process.

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framework of a policy’s stakeholders and the definition of general aims and means. At a strategic level, institutions act as a support for the ideas embodied by a paradigm. At an operational level, ideas and institutions act as an implementation mechanism of calibration and learning process. By applying this theory to the relationship between resource nationalism and public accountability, our research also intended to make a significant contribution to institutional policy analysis.

3   Literature Review Like most mineral endowed countries in the world, Latin American and Caribbean (LAC) oil and gas exporting countries face economical, social and political problems caused by fast and dramatic income variations— with commodity prices increasing during the 2000’s boom, and decreasing since the mid-2010’s with the end of the super-cycle of commodities (Gayi and Nkurunziza 2016). For instance, Venezuela is often cited as a exemplary case of the “institutional” resource curse (Corrales and Penfold 2011, 72), which posits a correlation between the abundance of natural resource rents and the weakness of political institutions, due to the negative economic feedbacks from these rents. As such, it shows that the effects of commodity price cycles on macro-economic performance depend on existing democratic institutions (Vera 2015). Early works on the political economy of natural resource endowment came after the 1973 and 1979 oil-price shocks. They were about the consequences of oil endowment for development, since oil exporting countries had experienced lower growth performances than oil-devoid countries during the early 1980s (Gelb et al. 1988). This counterintuitive observation partly contradicted the basics of neoclassical economics on comparative advantages as a determinant for international trade and development path. Further studies on mineral economies confirmed the negative relationship between resource abundance causing high variations of mineral rents, and economic development, which constitute the rationale of the resource curse thesis5 (Auty 1993; Karl 1997; Ross 2003). According to this theory, when mineral rents exceed a certain fraction of the gross domestic product (GDP), public spendings and total exports, they tend to unbalance the fiscal equilibrium by over-stretching public spendings and 5  For a review of the literature on the resource curse thesis, see Rosser (2006), and Ross (2012).

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by artificially reducing taxes, either directly (through tax reduction) or indirectly (through subsidies). Things go wrong when these rents shrink for price variations or stock exhaustion, due to the low elasticity of public spendings and the negative effects of the Dutch disease on the commercial balance and terms of trade. A second generation of scholars interested in resource endowment identified a negative correlation between mineral abundance and democracy, occasionally coming along with a positive correlation with violent conflicts (Ross 2001; Bannon and Collier 2003). On the one hand, mineral rents finance public spendings or support the accumulation of external debt, while alleviating fiscal pressure on citizens. On the other hand, they provide governments with extraordinary resources for patronage and actors engaged in illegal activities with huge sources of extortion and corruption. Although the causality between mineral endowment and authoritarianism is still subject to controversy in quantitative research (see Haber and Menaldo 2011; Dunning 2008), it cannot be completely discarded. As a matter of fact, many features of authoritarian and populist regimes— such as the lack of accountability and the discretional resource allocation used by the incumbent—do benefit from the increase of mineral prices and reserves. Likewise, many features of internal conflicts—such as access to point resources by illegal armed groups, who thus control strategic areas and infrastructures—are dramatically aggravated by commodity cycles. This lead to a third series of studies, aimed at explaining how institutions are affected by mineral boom and bust cycles, and how they allow governments to mitigate those effects (Humphreys et al. 2007a, b). The research agenda shifted from economic development to democratic governance, hence questioning the role of governments on development beyond the mere effects of production factors on development (Karl 2005; Auty and Gelb 2004). Scholars now commonly acknowledge that natural resource endowment is not a curse per se but rather comes from the existing political system regulating the economy, as well as the relationships between the State and the society, which can doom development prospects (Karl 2007; Stiglitz 2007; Kolstad et al. 2009; Bhattacharyya and Hodler 2011; Aytaç et al. 2016). Besides, it is the volatility of commodity prices rather than their absolute value, what constitutes a major challenge to any government because of its adverse effects on macroeconomic indicators and political institutions (Ross 2012; Timmerman 2012; Omgba 2015).

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Eventually, scholars started to question the role of governments in the management of commodity cycles, in particular through “resource nationalism” (Haslam and Heidrich 2016a). The resurgence of resource nationalism during the 2000’s oil windfall, especially in Latin America and the Caribbean (De Castro et  al. 2014), was a reaction to globalization and neoliberal policies of former decades (Veltmeyer 2012; Grugel and Riggirozzi 2012; Weitzman 2013; Koivumaeki 2015), and a way for governments to increase mineral rents through a better control of the extractive sector (Hogenboom 2012; Weijemars 2015). Resource nationalism is not a synonym for nationalization, since it can rely on a minimum participation of the sector by the State, through joint-venture and association contracts, or on a full control through direct exploitation by national companies (Haslam and Heidrich 2016b; Ghandi and Lin 2013). Neither is it a consequences of fast-growing oil prices (Mahdavi 2014; Cheon et  al. 2015), since it was initially a way to compensate for low prices by increasing the government-take in oil rents, occasionally through a major control over the volume of production (Berrios et al. 2010). Yet it was arguably fostered by the latest oil boom, due to the high leverage capacity acquired by the State in oil-exporting countries vis-à-vis multinational corporations and traditional OECD importing countries, particularly because of the growing demand from emerging economies such as China and India (Vivoda 2009, 2016). The general argument of the institutional version of the resource curse thesis is that commodity cycles have stronger effects on development and democracy when occurring in contexts of weak or unstable institutions. Hence institutions are essential to “escape the resource curse” (Humphreys et al. 2007a). Based on this now commonly accepted idea, five kinds of policy recommendations have been made, neither of which is exclusive from the others. The most radical is the non-exploitation of natural resources until institutions are sufficiently strong (Humphreys et  al. 2007b; Sachs 2007). More traditionally, some advise governments to create stabilization funds aimed at sparing during windfalls the money they may need in times of resource scarcity or prices downfalls (Kolstad et al. 2009). Conversely, governments are advised to reduce subsidies when commodity prices go down, in order to reduce public spendings and correct anomalies for further windfalls (Di Bella et al. 2015). Some scholars have also praised the benefits of direct distribution of the resource (Rodríguez et  al. 2012; Segal 2012). The minimalist agenda for policy change consists in increasing the State’s and companies’ accountability

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and control over natural resource rents by the civil society (Karl 2007; Ross 2012). The importance of public accountability in contemporary democratic governance is expressed by the diversification of formal and informal institutions regulating the relationships between the State, the society and markets. However, expecting institutions to solve the resource curse brings out more questions than answers for policy implications (Stevens and Dietsche 2008). Institutional change is a wicked problem, generally incremental and highly context-dependent: Existing institutions can help or constrain governments to control for exogenous factors such as oil prices, but these factors can dramatically affect existing institutions. Small-N comparative study and causal process tracing can help us to disentangle these factors, thereby overtaking the limits of the traditional political economy of the resource curse and its probabilistic stance.

4   Research Method The distinction between third-order change (paradigm shifts), second-­ order change (objectives and instruments change) and first-order change (instruments calibration) (Hall 1993), which provided the starting point of the process tracing of how resource nationalism hinders public accountability, was improved by separating policy ends and means at each level of action or policy contents (Cashore and Howlett 2007; Howlett and Cashore 2009; Howlett 2009), in order to clarify the causal mechanism linking changes in kind. These contents include the general goals and means at a normative level (3rd order change), the policy aims and objectives at a strategic level (2nd order change), and programs objectives and instruments settings at an operational level (1st order change). These can be described as the “ideational” aspects of policy change, structuring an overall governance mode, hereby defined as the way a government defines policy problems, social factors and political objectives (Pierre and Peters 2000, 201). Table  1.1 shows a typology of these aims and means for oil policy. We utilized policy instruments as empirically observable entities of a policy design, according to Christopher Hood’s taxonomy by the State’s resources of information nodality, authority, treasure and organization (see Hood 1986, 2007; Hood and Margetts 2007). Information nodality refers to the use and production of information by State agencies. Authority refers to formal rules expressed in the political constitution, laws and

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Table 1.1  Policy content by aims and means Normative level Policy ends Policy means

Economic development

Strategic level

Rent-seeking and national sovereignty Energy transition via Extraction production model change Demand-oriented transition

Operational level Increasing government-­ take from oil production Nationalist-oriented contractual regime Strategic alliances with foreign NOC Infrastructures construction

Source: Authors’ elaboration. Adapted from Hall (1993) and Howlett (2009, 275)

r­ egulations. Treasure refers to all financing sources and public spendings related to a policy area. Organization refers to all State and non-State agencies involved in the formulation, implementation and evaluation of a policy. Taken as a whole, these instruments define the substantial and procedural contents of the policy design, which refer to the distribution of goods and services by the State, and to the regulation of the relationships within a society and between the society and the State (Howlett 2011). Table 1.2 shows the taxonomy of selected oil policy instruments by the State’s resources. Once identified the core elements of a policy design to describe the template of public accountability related to oil policies in nationalist regimes, we were able to build a causal mechanism linking resource nationalism to public accountability deficits. We define a causal mechanism as “a system of interlocking parts that transmits causal forces from X to Y”, each part of which is an entity entering in activity to transmit a force that ends up producing the outcome to be explained (Beach and Pedersen 2013, 44 and 49). First we proceeded to a congruence analysis or a pathway regarding the mechanisms of public accountability deficits, through the definition of policy aims and means at three levels (normative, strategic and operational). Then we performed a series of hoop tests6 in order to confirm or disconfirm the existence of a causal relationship between nationalist ideas and policy outcomes for public accountability. 6  On process-tracing tests, see (Beach and Pedersen 2013; Bennett 2010; Collier 2011). A hoop test is used in process-tracing to prove insufficient but necessary causal hypothesis. When passing the test, the hypothesis is relevant but it cannot be confirmed; when failing it, it can be eliminated (Bennett 2010, 210).

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Table 1.2  A taxonomy of oil policy instruments according to the State’s resources Information nodality

Authority

Treasure

Organization

Information systems Technical assessments

Political constitutions

Contracts

Ordinary laws and regulation

National planning

International laws

International programs (EITI, NRGI)

International law agencies (International Center for Settlement of Investment Disputes)

Rent management systems Foreign direct investments International prices

National oil companies State agencies

Local governments International organizations

Source: Authors’ elaboration. Adapted from Hood (1986) and Howlett et al. (2009)

Eventually we improved the identified causal mechanism through small-N comparison based on John Stuart Mill’s methods of “differences” and “agreement” (Mill 1843). The method of differences consists in comparing cases that differ with respect to the cause (X) or the outcome (Y) but do not differ across comparable cases with respect to other variables or factors.7 The objective here is to identify the factors that can produce differences among similar systems. The method of agreement consists in comparing cases to detect the relationships between X and Y that remain similar, in spite of differences in other features of the cases being compared.8 It is used to identify necessary conditions to similar outcomes in different contexts. These protocols can be applied in different ways, whether the research design is case-oriented (to compare systems) or variable-oriented (to compare units of a system) (Collier et  al. 2010, 145; Beach and Pedersen 2013, 77; Peters 2013, 40). In practical terms, each protocol works ­differently to explain causality, with the former following a principle of 7  In Mill’s words: “If an instance in which the phenomenon under investigation occurs, and an instance in which it does not occur, have every circumstance save one in common, that one occurring only in the former; the circumstance in which alone the two instances differ, is the effect, or cause, or a necessary part of the cause, of the phenomenon” (Mill 1843, 455–456). 8  In Mill’s words: “If two or more instances of the phenomenon under investigation have only one circumstance in common, the circumstance in which alone all the instances agree, is the cause (or effect) of the given phenomenon” (Mill 1843, 453).

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sufficiency (the “ceteris paribus” clause) and the latter a principle of necessity (the “no matter what” clause) (Keman 2014, 54–55). Both are akin to a “causes-of-effects” approach (Goertz and Mahoney 2012, 42) that explains outcomes or study the effects of particular causal factors in individual cases or small-n sets of cases. In the present research we compared two countries where radical reforms were implemented, in order to identify the causal mechanism linking resource nationalism to public accountability deficits (thus engaging in theory-building and testing). Then we compared two countries where reforms were implemented, in order to identify the deviant point of this causal mechanism which could explain when resource nationalism does not cause a public accountability deficit (thus engaging in theory reformulation). Data were gathered from institutional sources (governmental and non-­ governmental), through document revision and semi-directed interviews to State and non-State actors. Interviews to civil servants involved in oil policy, representative of accountability agencies, scholars and civil society activists were conducted in four countries.

5   Book Organization The book is organized in four chapters besides the present introduction and the concluding section. Chapter 2 presents the policy design framework which provided the theoretical background of our research. It builds on a typology of the foreground theories of policy design based on four methodologies: neo-positivism, realism, analyticism and reflexivism. Chapter 3 presents the realist approach that provided our analytical framework. It defines the causal mechanism of a policy outcome from a realist methodology, then it displays a method of cross-case comparison for policy design, including the case selection, and it unpacks the causal mechanism linking resource nationalism to a deficit of public accountability. Chapter 4 presents a congruence analysis for the theory building of the causal mechanism presented in Chap. 2, based on two typical cases (Venezuela and Ecuador) and two deviant cases (Mexico and Brazil). It puts resource nationalism in the historical perspective of extractive models of development experienced in Latin America, before explaining the differences between closed and open resource nationalism, and how these differences affect public accountability. Chapter 5 presents the results of a deep within-case study of closed nationalism, based on the Chavez admin-

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istration in Venezuela (1999–2012). It analyzes the evidence collected for each entity of the causal mechanism tested in Chap. 3, including the agenda setting, the policy formulation, the institutional change, the political interplays and the policy outcome for public accountability. Chapter 6 presents the empirical findings and the theoretical implications of our research. It emphasizes the role of institutions in policy design and makes recommendations to improve public accountability in oil producing countries.

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CHAPTER 2

The Policy Design Framework

1   Introduction: The Shift to Policy Design During the 1980s comparative policy analysis (hereafter CPA) experienced a shift from social theory to policy design, turning its focus towards explaining policy outcomes by previous decisions regarding policy problems and solutions (Linder and Peters 1984). From then on scholars would map policy outcomes according to normative scales, and provide practitioners with new inputs regarding the selection of policy instruments. Since then they have produced many different theories of the policy design, related to agenda-setting, implementation gaps, policy and institutional change, and so on and so forth. A common feature to these theories is that they express a government’s decision based on causation, instrumentation, evaluation and intervention (Peters 2018, 20–23). Causation refers to the understanding of the causes of a policy problem; instrumentation refers to the selection of policy instruments to address this problem; evaluation is the assessment of the values that a government seeks to achieve through the policy design; and intervention is the way a government makes a policy work through public administration. Taken as a whole, each model of causation, instrumentation, evaluation and intervention is likely to be assimilated to a policy paradigm which provides guidance to the government (Hall 1993). Initial works underlined the similarities with design in architecture and engineering, such as context sensitivity, tools application, human agency © The Author(s) 2020 G. Fontaine et al., The Politics of Public Accountability, International Series on Public Policy, https://doi.org/10.1007/978-3-030-28995-9_2

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and values pursuing (Bobrow and Dryzek 1987, 200). They also stressed out the utility of CPA for policy design to improve decisions, both by avoiding biases in the instruments selection and by suggesting a formal, self-conscious search and selection process (Schneider and Ingram 1988). Later on the democratic governance literature would draw scholars’ attention on the complexity of policy instrumentation (Peters and Van Nispen 1998; Salamon 2005; Eliadis et  al. 2005; Howlett et  al. 2009). This brought in the typological theorization of policy instruments, and it placed the institutional change at the heart of policy design. A third generation of “conscious” policy design (Howlett and Lejano 2012) came at age in the late 2000s. As in echo to the new public management, this “new” policy design (Howlett 2014; Howlett et al. 2014) deals with emerging research questions about the mix of policy instruments and policy portfolios, the role of experts assessments in evidence-based policy making, the relationship between technical knowledge and political ideas, the context of decision making and the modalities of institutional change. However some scholars contend that the rational-instrumental logic behind this theory can hardly account for the complexity of democratic governance (Turnbull 2017). They recall that policy design is more a craft than a scientific activity (Tinbergen 1958, cited in Bobrow 2006), in particular because policy making is the result of a continuous flow of decisions made under pressure by governments and involving multiple stakeholders (Colebatch 2017). Hence policy design cannot be reduced to one theory or another, as if the “new” policy design was an improvement compared to the “old” one. The “new” policy design may as well be the latest transformation of a ubiquitous, necessary and difficult activity (Bobrow 2006) resulting in a continuous production of theories and methods. Is it accurate then to refer to a policy design framework? It is, as long as we understand a “framework” as a general form of analysis that provides a meta-theoretical language to compare theories (Ostrom 2011). Drawing on Peters (2018), in this chapter we contend that the theoretical pluralism engendered by the shift from social theory to policy design in CPA can be organized around four models of causation, intervention, evaluation and instrumentation defined by scholars’ methodologies. Section 2 presents a typology of these methodologies, based on different philosophical and scientific ontologies (Jackson 2016), and their implications for the research on policy design. Section 3 explains how the four models that we coin “instrumentation”, “institutionalization”, “framing” and “emancipation”

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are related both to these methodologies and to middle-range theories of the policy design.

2   Aligning Ontology and Methodology in Policy Design 2.1   A Typology of Policy Design Approaches The policy design framework does not refer to any substantial theory but rather to their complementary existence and their respective contributions to research and practice (Peters 2018). It is as encompassing a framework as the policy cycle (Jones 1984). Yet unlike the latter, policy design has a normative orientation to explain or interpret the interplays between a policy’s actors, context and instruments: “The idea of design is to link together values, models of causation, and the choice of instrumentation so that better choices can be made” (Linder and Peters 1987, 468). Through this normative orientation, it turns into a “conscious” activity aimed at coping with the biases due to actors’ intervention and instruments mismatch (Linder and Peters 1990a). It proceeds with ordering familiar actors and instruments through procedural criteria, and assessing various combinations of actors and instruments through substantive criteria (Linder and Peters 1991). Policy design is first and foremost the result of continuous changes (either incremental or revolutionary) in the rules of governance and the proliferation of complex or wicked problems (Peters 2018). Therefore the problem of instrumentation—that is to say the creation, selection and combination of tools to achieve policy aims—is at the core of policy design (Lascoumes and Le Galés 2007). Of all policy instruments classifications the most widespread rests upon the State’s resources of nodality, authority, treasure and organization (Hood 1986). Nodality refers to the government’s position amidst information networks; authority refers to the official power and the production of legal norms by the State; treasure refers to the available financial resources and the power to emit money; organization refers to the State’s administrative capacity based on human and physical resources (Hood 1986, 4–6). The combination of policy instruments as detectors and effectors produces a virtually infinite number of policy mixes (Hood 1986, 117; Hood and Margetts 2007, 147) so, when designing policies, instead of starting from scratch a government would

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rather adapt to the changing context by altering a policy’s aims and means (Howlett 2009). Yet there are as many theories of policy instrumentation as there are of policy design, and the literature shows there are many different ways to use this taxonomy, whether instruments are conceived as discrete entities or as general conceptual categories of empirical observations (Hood 2007). After all, policy design is the subject of many conceptions and interpretations among State agencies, experts and scholars, and the publics involved in a policy area (May 2005). Consequently scholars and practitioners may disagree on how to cope with it because of their discrepancies regarding the importance of choice, context, frames and power. Therefore improving policy outcomes can either result from selecting and combining the right instruments to achieve the right aims or goals (Howlett 2011), or involving non-State actors in the agenda-setting, the policy formulation and its implementation through a framing process (Hoppe et al. 1987) or even de-constructing the power relationships embodied by policy instruments, in order to foster citizens emancipation (Bobrow and Dryzek 1987). These theories are grounded in different methodologies, which refer to “a concern with the logical structure and procedure of scientific enquiry” (Sartori 1970, 1033), and they call for different methods, the techniques for gathering information. A methodology is defined by the combination of a philosophical ontology (i.e. a conception of the mind-world relationship) and a scientific ontology (i.e. a conception of the knowledge on the world) (Sayer 1992; Jackson 2016). This distinction goes against the “epistemic fallacy” (Bhaskar 1978, 26) according to which a statement about the world can be reduced to a statement about knowledge. Scholars’ philosophical ontology will be dualist or monist, whether they see the world as separate from the mind or not. Their scientific ontology will be phenomenalist or transfactual, whether they ground their knowledge on directly observable or on non-observable but detectable phenomena. Table 2.1 displays a typology based on these ontologies, where “neo-­ positivism” combines dualism and phenomenalism, “critical realism” combines dualism and transfactualism, “analyticism” combines monism and phenomenalism, and “reflexivism” combines monism and transfactualism (Jackson 2016). This typology is both exhaustive and excluding, so it goes beyond the dilemmas of positivism versus interpretivism (King et al. 1994) or empiricism versus post-empiricism (Fischer 2004), avoiding any “mixed” or “miscellaneous” category of cases. It does not conflate methods and tech-

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Table 2.1  Four methodologies Scientific ontology

Philosophical ontology

Dualist Monist

Phenomenalist

Transfactual

Neo-positivism Analyticism

Critical realism Reflexivity

Source: Jackson (2016)

niques with methodology (but see Hall 2003) nor does it confound methodological with theoretical issues in a deterministic relationship between ontology, epistemology and methods (but see Marsh and Furlong 2010). Unlike dualists, monists do not conceive there is a mind-world gap to bridge with scientific knowledge, so that an epistemology cannot exist from that standpoint (Jackson 2016, 34). Ideally speaking, when choosing their research methods, scholars should consider making explicit both their conception of policy design and their conception of knowledge about policy design. This choice depends on whether they believe that the mind mirrors the world or that it is continuous with it, and whether they believe what they see is the only knowledge that matters or that there is something beyond what they see that explains what they see. On one hand monists share a common conception of the world as continuous with the mind, so they settle for producing interpretations based on their experience. However they proceed differently, according to their treating knowledge as phenomenological or transfactual. On the other hand dualists share a common conception of the world as separate from the mind, hence their will to produce causal explanations. However they may also proceed differently according to their scientific ontology. 2.2  Methodological Implications for Policy Design The four methodologies described above have different implications for CPA and the policy design framework, regarding the logic of causation, the aims of intervention, the modalities of evaluation and the results of instrumentation. Table 2.2 displays these methodological implications. By aiming at falsifying law-like theories, neo-positivism produces variable-­oriented explanations of the world. It proceeds by the counterfactual analysis of observable phenomena which are eventually integrated

Source: Elaborated by the authors, adapted from Jackson (2016)

Reflexivism

Analyticism

Realism

Logic of causation

Variable-oriented explanation Institutional web of Case-oriented interactions explanation Framing process Variable-oriented interpretation Emancipatory process Case-oriented interpretation

Foreground theory of the policy design

Neopositivism Instruments selection

Methodology Law-like theories falsation Middle-range theory building and testing Ideal-type theory building and testing Critical theory testing

Aims of intervention

Counterfactual analysis of observable data Transfactual analysis of non-observable data Counterfactual analysis of observable data Transfactual analysis of non-observable data

Modalities of evaluation

Table 2.2  Methodological implications of different ontologies for policy design

Narratives

Contingent patterns Typologies

Predictive models

Results of instrumentation

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into predictive models. So aligning their methods with this methodology have scholars conducting nomothetic variable-oriented comparisons as a way of testing covariation (Jackson 2016, 55 and 81), which is consistent with a probabilistic conception of causation. This entails a preference for experiments and large-n comparison to control for independent variables. They may also engage in deep within-case studies conducted in a deductive fashion, to apply or to “test” general rules deduced from large-n comparison. In absence of a laboratory to conduct experiments and control for these variables, multiple cases are used as proxies (Breuning and Ahlqvist 2014) and compared through most-similar and most-different systems design (Przeworski and Teune 1970), a quantitative translation of the methods of differences and agreement (Mill 1843). By aiming at middle-range theory building and testing, realism produces contextual explanations. It proceeds by the transfactual analysis of non-observable phenomena which are included in contingent patterns of causation. When aligning their methods with this methodology, scholars conduct contrasting case-oriented comparisons as natural experiments to elucidating causal powers (Jackson 2016, 56), which is consistent with a deterministic logic of causation. Hence they are most compelling when engaging in small-n comparison and deep account of typical or influential case studies. In absence of a laboratory, fuzzy-set QCA (Rihoux et  al. 2011), process tracing or a combination of both (Schneider and Rohlfing 2013; Beach 2018) may serve to eliminate non-explicative factors and to identify causal mechanisms as combinations of factors explaining particular outcomes (Beach and Pedersen 2016). By aiming at an ideal-type theorization, analyticism produces variable-­ oriented interpretations of the world. It proceeds by the counterfactual analysis of observable phenomena which are then organized in typologies. For analyticists, knowledge is at best a useful ordering experience, since there is no mind-independent world against which a theory can be tested (Jackson 2016, 56). Here cross-case comparison is no strategy of inquiry because an ideal-type has no discrete empirical counterpart: it is only a general analytical claim that can eventually be clarified through inductive comparison. Hence it may combine large-n comparison with deep within-­ case studies in an inductive fashion that consists in calibrating ideal types rather than “testing” them against empirical data. On one hand, scholars may conduct individualizing variable-oriented comparison in order to specify, refine or calibrate particular configurations of causal factors, following a probabilistic logic of causation. On the other hand, they may

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develop “singular causal analyses” by using ideal-types to understand what happened in a particular case (Jackson 2016, 161). The necessity of a causal factor is assessed counterfactually through an alternative pathway built on historical methods, descriptive statistics or heuristic (Yanow 2013). Last but not least, by aiming at theorizing their own social condition, reflexivist scholars produce case-oriented interpretations, based on a critical interpretation of the world (Jackson 2016, 56). This comes after “the problem of intellectuals” or the concern for what scholars do when they produce knowledge about the world (Jackson 2016, 187). They proceed by the transfactual analysis of non-observable phenomena which are then organized and presented into narratives. Although comparison is no research strategy to them, they may replicate and compare within-case studies about common issues (such as gender, class, ecology, development, etc.). Therefore they may either engage in small-n comparison to confirm their theories, or conduct incorporating case-oriented comparison to provoke social change, in accordance with a deterministic logic of causality. 2.3  Four Models of Causation, Intervention, Evaluation and Instrumentation Based on this typology, four conspicuous models of causation, intervention, evaluation and instrumentation can be built in order to organize the state of the art on the policy design literature. Far from converging into a grand theory of policy design, these models coexist and challenge one another because they are grounded in different methodologies (Fig. 2.1). The “instrumentation model” is grounded in the neo-positivist methodology inasmuch as it defines causation in predictive terms that can only be proven with regularities via covariance. The “institutionalization model” is grounded in realism because it defines causation in terms of dispositional theories based on elucidating causal forces via INUS complexes (Mackie 1965). The “framing model” is grounded in analyticism since it defines causation in configurational terms based on ideal-types which are elaborated via counterfactual analysis. The “emancipation” model is grounded in reflexivism as it defines causation in dialectical terms based on an understanding of social structures via hermeneutic. The following section offers a synthesis of the foreground theories of the policy design according to these models.

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Scientific ontology Phenomenalism

Transfactualism

Regularities via covariance

Causal forces via INUS complexes

Based on

Based on

Dispositional causation

Dualism

Predictive causation

Explain

Explain

Philosophical ontology

Policy design as instrumentation

Policy design as institutionalization Propositional knowledge (aims of comparative policy analysis)

Policy design as framing

Policy design as emancipation

Monism

Interprete

Configurational causation Based on Ideal-types via counterfactuals

Fig. 2.1  A typology of policy design models

Interprete

Dialectical causation

Based on Social structures via hermeneutic

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3   Foreground Theories of the Policy Design 3.1  Policy Design as Emancipation The first model defines policy design as an emancipation process in which problem definition is linked to a policy outcome through interpretive exercises involving the design itself, the policy adoption, the implementation and changes in targets and intermediate products (Bobrow 2006). Here causation results from a dialectical interpretation achieved through the disclosure of unresolved tensions in an open system. Evaluation is carried out through the assessment of policy instruments as normative concepts. Intervention relies on prescriptive heuristic and deliberative analysis grounded in political philosophy and critical theory. As in the framing model presented below, policy instruments are means for the government to influence non-State actors’ behaviors through coercion or incentives. Yet unlike analyticists, reflexivists understand policy instruments as causal forces at play in an endless argument over contingency, values and priorities to be attended by a policy. This model states that policies result from the production of a socially situated knowledge on the interactions between values, context and audience. From that standpoint, policy design is an emancipatory strategy in the power relationships opposing non-State actors to the State. Scholars aim at producing useful (prescriptive) accounts through analytical narratives, in order to identify general patterns of social interactions between political and administrative agents (State actors) and social and economic agents (non-State actors). From that standpoint, policy design is both a consequence of the political context and a determinant of the societal context. In the emancipation model, a policy is the product of a problem definition based on value clarification, causalities and current realities (Fig. 2.2).

Politics

Policy design, formulation, adoption

Policy implementation, service delivery

Target group beliefs, behavior

Fig. 2.2  The policy design as emancipation model. (Source: Adapted from Bobrow 2006, 84)

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It is an iterative process leading to a policy adoption, implementation and outcomes, during which State and non-State actors confront their interpretations of the policy aims and means. At each moment these interactions produce feedback effects on the policy design, adoption and implementation. Depending on the interpretation of the adopted policy, the implementation goes through changes in the human and organizational activity or in the chains of consequences. Either way, the implementation produces a change in the policy targets and intermediate products. Again, the interpretation of the result produces changes in the valued outcomes, which then feeds back the problem definition and starts a new cycle in the policy design. The emancipation model stems from the question of how to account for the diversity of frameworks conveyed in a policy design. The central argument is that these frameworks are the combination of distinct epistemologies with different technical frames. The actors involved in a policy area refer to different technical frames of reference—such as welfare economics, public choice, social structural approach, information processing and political philosophy—which drive their conception of a policy area’s problems and solutions (Bobrow and Dryzek 1987, 16–17). Welfare economics are rooted in micro-economy and develop cost-benefit analysis based on neoclassical economics to address market failures through public policies. Public choice combines micro-economy with political science and public administration, and it applies rational choice theories to State agencies and agendas in order to address government failures through institutional design (market and public sector). The social structure approach (or structuralism) comes from sociology and political science and applies a sociological reasoning to public policy contents in order to inform the consequences of the government distributing goods to individuals and groups. Information processing comes from multiple disciplines (ranging from cognitive psychology to artificial intelligence) and develops decision-­ making models (such as cybernetics, the human brain, the computer or the garbage can) in order to address the problems raised by bounded rationality when individuals and organizations make choices or take decisions. Political philosophy combines philosophy with political science and law, and develops theories of the government’s responsibility and human agency, in order to address the moral implications of policy processes for liberal principles. These actors speak out from four “epistemologies” (sic)—coined positivism, social engineering, relativism and reasoned consensus—which

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define their conception of knowledge regarding policy design. Positivism and piecemeal social engineering share the belief in causal laws invariable across time but they proceed differently and have a different confidence in their theories (Bobrow and Dryzek 1987, 122–140). On one hand positivism would use public choice and welfare economics to explain causally and solve social problems in a law-like fashion. It would recommend to wait and see until a law is found, therefore it would rather trust experts and scientists to take more rational decisions. On the other hand piecemeal social engineering would rather use experiments or quasi-­experiments to falsify theories of the policy process which are compatible with information processing and political philosophy but not with public choice, welfare economics or structuralism. It would proceed by trial-error and verify hypotheses but it would allow more participation and legitimacy of non-­ experts. However these techniques are limited when it comes to policy design. First, the causal invariance during experiments makes it useless to face rapid change and helpless to explain it. Second, there is a possibility that a government’s intervention may undermine the conditions described by its laws. Third, they treat any policy as instrumental to some aim. Fourth, the agency of social actors is not taken into account to explain choices. Fifth, complexity is not decomposable. Considering these limitations, relativism and reasoned consensus offer some solutions to policy design in theory and practice (Bobrow and Dryzek 1987, 149–182). Relativism combines various frames to inform a decision in an eclectic or a forensic fashion, comparable to Kuhn’s paradigms. Eclectic relativism uses storytelling by mixing positive and normative statements, compatible with social structure practice (such as heuristic stimulation). Forensic relativism seeks to combine coherence, congruence and cogency to construct a rational ideology, a pluralistic system free of dogma, based on a checklist of the points contained by a policy argument. It can be combined with all technical frames except political philosophy. Reasoned consensus can be achieved by accommodation or by critical policy analysis. Accommodation is a way to reach consensus on a worldview interpretation but it’s like a dismissal since one actor (generally the less powerful one) renounces to speak the truth to power. It can also be achieve through an “evaluability assessment” (idem, 164) by which both parts work together on problems definition, goals, realistic indicators (etc.) to improve the performance rather than decide the termination of a policy. It is not compatible with the four technical frames described above,

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so it would rather get along with individual social structure, decision analysis and pessimistic information processing. Eventually reasoned consensus can be achieved through critical policy analysis aimed at correcting the systematically distorted communication established by the unbalance of power among actors, even before a consensus on values is reached. It follows a four-step pathway including dialectics (through a clash of viewpoints or frame), individuals and groups’ capacities equalization (regarding access to information, etc.), prototyping or holistic experimentation (through multi-stakeholders participation) and institutional innovation (such as mediation and broad scale discursive exercises). Critical policy analysis is hardly compatible with welfare economics, public choice and individual structuralism (considered top-down manipulation instruments) and with information processing (considered favoring the political status quo). But it combines with political philosophy (critical or reflexive) except with the utilitarian theories of State-­ society relationships. Policy design shares similarities with design in architecture and engineering, such as its context-sensitivity, tools application, human agency and value pursuing. But it has its specificities regarding fluid environment, complex problems and aims, and conflicts of values and interests: “Design is the creation of an actionable form to promote valued outcomes in a particular context” (Bobrow and Dryzek 1987, 201). Hence a four-step procedure which consists in: (1) addressing values according to timing, amount and priority; (2) capturing the context through complexity and uncertainty, potential feedbacks, control, stability and audience; (3) selecting the appropriate approaches to address the relevant values and factors that determine a policy outcomes; and (4) applying the appropriate approach based on gathering and interpreting the information needed, the invention and stipulation of policy alternatives, the assessment and comparison of policy alternatives, and the construction of arrangements. This model constituted a major breakthrough in policy studies which contributed to the shift from social theory to policy design. It tended a bridge between theory and practice and it called for caution with methodological alignment. However it relies on a confusing distinction between epistemological approaches, technical frames. Practically and theoretically, its typology of theories of knowledge (Bobrow and Dryzek 1987, 186) is of little help when it comes to interpret policy problems and possible solutions, since it ends up with too many indeterminate assumption regarding the compatibility of technical frames with different epistemologies. Critical

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policy analysis is particularly difficult to relate to policy design, since it is incompatible with welfare economics and public choice, while its compatibility with structuralism and information processing remains doubtful. Scholars from this school of thought embraced the “argumentative turn” and the introduction of the critical theory in public administration and planning (Fischer and Forester 1993; Forester 1993). Against the hegemony of instrumental rationality in social sciences, they started advocating for a cognitive approach to the policy process, consistent with the theory of rational-critical communication (Habermas 1984). This implied a preference for heuristic, deliberative analysis and thick descriptions of historical events (Yanow 2013). Later on the focus on the relationship between policy design and the sociological locus of the researcher derived in theories of the narrative policy analysis (Roe 1994), participatory problem-­solving (Pahl-Wostl 2002), deliberation and practice (Fischer 2003, 2004, 2007). Ultimately some scholars strongly objected to the “new policy design” theory, as they consider policy design is produced by bottom-up practices rather than top-down rational decisions (Turnbull 2017). 3.2  Policy Design as Framing The second model defines policy design as a framing process, which links politics to target groups’ beliefs and behaviors through policy formulation, adoption and implementation or service delivery (Hoppe 2014, 7). Here causation is conceived as a configurational interpretation through counterfactual analysis; evaluation is carried out through the interpretation of policy instruments as cognitive representations; and intervention rests upon the analytical oversimplification of real situations (ideal-­typification) to guide the policy co-construction by State and non-­State actors. Analyticists place actors’ perceptions, representations and interpretations at the core of the policy design. From that standpoint, the conceptual distinction between policy analysis and policy design makes little sense (Ingram and Schneider 2008). As in the instrumentation model described below, policy instruments are the means upon which the government relies to establish their authority and legitimacy. Ideas are pervasive in the translation, framing and designing dynamics. But since they cannot be abstracted from the actors’ perceptions and values, they can hardly be conceptualized as dependent or independent variables. In the framing model policy design is produced by the interactions between political actors and policy targets (Fig.  2.3). Based on their

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Problem definition: value clarification, causalities, current realities

Policy design

Interpretation

Policy adoption

yes

no

Interpretation

Implementation through changes in human and organizational activity

Implementation through changes in chains of consequences Interpretation

Change in targets, intermediate products Interpretation

Changes in valued out comes

Interpretation

Fig. 2.3  The policy design as framing model. (Source: Adapted from Hoppe 2014, 7)

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i­nterpretation of a policy problem, citizens, organizations and professional communities play an active role in the adoption of a solution and the service delivery. The result is a transformation of policy problems from undesirable situations to opportunities for improvement, by which they have the government adjusting their aims and means. This model stems from the question of how society is affected by policy design. The substance of public policies is “a purposeful and normative enterprise [based on] underlying patterns and logics” whose consequences depend mainly on meaning and interpretations that constitute “the social construction of the policy in value dimensions” (Schneider and Ingram 1997, 3). The central argument is that when a policy design discourages active citizenship it prevents the creation of self-correcting mechanisms to attend policy failures. This is the expression of a “degenerative form of politics” (idem 1997, 6), in which issues and target populations are socially constructed and strategically manipulated. The government favors scientific and professional criteria over political ones, hence contributing to the political system’s apathy and the legitimacy crisis like the one faced by the US government in the 1990s. According to this approach, the traditional theories of public policy are unable to explain such a crisis. Pluralist theories uncritically accept the modalities of delegative democracy and restrain the role of the government to protecting fundamental rights and be responsive and accountable. Most theories of the policy sciences focus on expertise, professionalism, evaluation research and scientific studies of the policy process. Others, like the public choice school, contend that market outperforms government and therefore justify deregulation, privatization and downsizing public administration. Eventually critical theory considers the root problems to be the fundamental structural features of social, political and economic systems. The framing model builds on a three-part system linking a policy design with a societal context and an issue context through framing, designing and translation dynamics (Schneider and Ingram 1997, 73–81). Policy design is defined by socially constructed goals and problems, agents and implementation structures, targets, rules and tools, and rationales and assumptions. The societal context refers to citizenship, democratic values, justice and problem solving. The issue context refers to the types of target groups, the distribution of political power, and existing institutions and institutional culture. The societal context and the issue context are linked by framing dynamics, which consist in interpreting the events, groups’

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knowledge and societal conditions. The issue context is linked to the policy design by designing dynamics, which consist in (re)framing issues, setting agendas, calculating risks, exercising leadership, analyzing policies and copying or creating designs. The policy design is linked to the societal context through translation dynamics applied to experiences, messages, lessons, conceptions of the government and role of citizens, and participation patterns. In the policy design as framing model the effectiveness of a policy depends on how it is coproduced by the target population through the translation dynamics linking a policy design to the societal context in order to define the goals and problems to be solved (idem 1997, 81–101). In these dynamics agents and implementation structures (which are the means to deliver a policy) interact with the target populations by means of the policy tools used by a government to make agents do something they would not do otherwise, the rules or procedural aspects of policy design, and the rationales (the explanations, justifications and legitimations of a policy design). Based on this framework, the theory of degenerative politics states that each set of dynamics has a negative effect on specific individuals and groups, which are particularly noticeable through the status of knowledge in policy design (idem 1997, 104–106). In order to serve the interests of politics, targets and experts, framing dynamics define issues in scientific and technical terms according to an instrumental rationality. To benefit the powerful and burden the powerless, designing dynamics have policy makers defer to scientific and professional judgement. And to empower target populations and exclude others, translation dynamics marginalize ordinary citizens and disregard common sense while political reasoning is disqualified by scientist and professionals. Eventually policy design has different effects on the social groups defined by their political power and the status assigned to them by the government (idem 1997, 109), which can be measured through public spendings. Those who enjoy stronger political power are advantaged if considered “deserving” by the government and “contenders” if not. The weaker ones become “dependent” when they are considered deserving and “deviant” when they are not. The same typology serves to define whether the benefits or burdens distributed by the government are risky or constitute a political opportunity. Changes in these categories can come from external factors such as institutions, policies from other areas, elections, narratives and learning, or from internal ones such as organizing

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and mobilizing to advocate, group attributes (size, resources, behavior, etc.) and political, moral or policy entrepreneurs (Pierce et al. 2014). Policy design as framing is an abiding intellectual and political process of puzzling and powering which consists in structuring unstructured problems through iterative bargaining and discussion about the meaning of policy problems and solutions (Hoppe 2017). From this standpoint agents and implementation structures are social constructions that interact with the targeted populations to deliver a policy. Policy aims and problems are socially constructed by State and non-State actors according to individuals’ perceptions of existing conditions. Initially scholars from this tradition addressed the problem of disconnected cognitive levels and maps between policy “designers”, implementors and target groups (Hoppe et al. 1987). Thus policy design was above all a way to make actors do something they would not do otherwise, using policy instruments to influence their behavior towards compliance (Schneider and Ingram 1990). The research agenda then turned to how policy design shapes the social construction of the population targeted by a policy, according to their identity and power (Schneider and Ingram 1993, 336). This lead to the theory of the “degenerative policy design” (Schneider and Ingram 1997), with framing and translation at the heart of the unbalanced relationships between the government, the intervening experts and the targeted public. Further studies addressed the drivers of change in targeted populations, or how the status of these actors could evolve from one category to another, which is akin to the research conducted under the advocacy coalition framework (Pierce et  al. 2014, 19–20). Most recent scholarship deals with the “design talk” in the process of governing, which refers to policy design as a framing activity in the practice and analysis of policy (Colebatch 2017). 3.3  Policy Design as Instrumentation The third model conceives policy design as an instrumentation process that conveys rational actors from within and outside the State apparatus. It stems from the question of how to combine macro- and micro-levels of policy design. Here causation is explained through empirical generalizations conceived as nomothetic (law-like) theories in a closed system; evaluation is based on the assessment of policy instruments as substantive data (phenomena) expressing the rational choices made by the actors involved;

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and intervention rests upon evidence-based knowledge produced by experts and experimental assessments. Policy design as instrumentation is both embedding—as it conceives policy design as a nested multi-level process—and variable-oriented—as each part of the process can be isolated theoretically from the others to be controlled. It settles an ambitious neo-positivist agenda that continues former policy studies, according to which policy design consists in matching aims and means through instruments mix (Del Río and Howlett 2013; Howlett et  al. 2014), to improve policy outcomes at macro, meso and micro levels. Policy instruments are conceptualized as a product of actors’ instrumental rationality the “dependent variables” of policy change (Howlett and Cashore 2009), while interests, ideas and institutions are its independent variables (Béland and Cox 2013; Kern et al. 2014; Daigneault 2014; Hogan and Howlett 2015; Wilder 2015). The instrumentation model of policy design links a governance mode to tool calibration criteria, through instruments selection, policy implementation and choice criteria (Fig. 2.4). The central argument is that several modes of governance can co-exist at the sectorial level, therefore we need a more systematic understanding of policy choices at a micro-level, to improve our understanding of policy design (Howlett 2011, 10). A governance mode defines a policy implementation style through its instruments at three levels. At a macro level general governance goals and means are defined by constituent policies; at a meso level sectorial policies are formulated and implemented through instrument mixes; at a micro level, these instruments are calibrated during programs design and implementation (Howlett 2004, 2005). A governance mode may be either legal, corporatist, market driven or network driven (Considine 2002) according to the degree of hierarchy/participation and centralization/decentralization featuring the relationships between structures and agency (Howlett

Governance mode

Policy tools available at each stage of the policy cycle

Implementation instruments available in a policy regime

Choice criteria

Tool calibration criteria

Fig. 2.4  The policy design as instrumentation model. (Source: Adapted from Howlett 2011, 56)

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2009b). The policy cycle refers to the Lasswellian approach in the policy sciences, which makes a heuristic distinction between agenda setting, policy formulation, decision making, implementation and evolution. Implementation instruments are defined by the State’s resources of nodality, authority, treasure and organization (Hood 1986), to which a distinction between substantive and procedural instruments is added (Howlett 2011). Substantive instruments refer to a government’s capacity to distribute goods and services, and procedural instruments refer to their capacity to control the relationships between State and non-State actors. Eventually the choice and calibration of policy instruments depend on a multi-criteria analysis to appraise their visibility, availability, cost, automaticity and targeting precision. The question raised by this tool approach is twofold: What are the consequences of policy instruments on the effectiveness of government programs? And how are instruments choices defined? From that standpoint research on policy instruments has gone through five steps, from the inventory of individual instruments, to classifications, then to theorization and model building and testing, eventually to prescriptive studies (Howlett 2011, 41–61). The 40 or so stocktake of the economic policy instruments carried out by early research have been enriched by market and hybrid policy instruments brought in by new public management. In the meantime, intents of classifications were successively based on instruments’ coercion, as sticks and carrots, instruments’ enforcement, inducement and benefaction effects, by governing resources, or qualified as mandates, inducements, capacity-building and system-changing. Likewise instruments theorization has evolved from the identification of the key determinants of instruments choice in the economic policy (economic objectives, structural and conjectural context, technical ground, political preferences, institutional limitations of the political system), to tool preferability between public/private companies and agencies, persuasive/compulsory quality, direct/indirect control over expenditures, voluntary/compulsory organizations membership and autonomous/responsible government agencies, then to a combination of preferability and coercion (degree of coercion, self-/full regulation). Traditionally, neo-positivist approaches to CPA make an extensive use of cost-benefit analysis and econometric modelization (Weimer 1992; Weimer and Vining 2004), semi-experiments (John 2012), time-pooled series (Jones and Baumgartner 2004) and formal process tracing (Falleti and Lynch 2009). Neo-positivist policy design is akin to this tradition

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when it focuses on program design (Del Río and Cerdá 2017; Rogge et al. 2017) and nomothetic theories of policy change (John 2003; Rayner 2009; Howlett 2009a; Boushey 2013), implementation styles (Linquist 2006; Howlett and Rayner 2007, 2013), government efficiency, coherence and congruence in policy formulation (Tosun and Treib 2018), and instruments constituency through policy mixes, portfolios or bundles (Varone and Aebischer 2001; Landry and Varone 2005; Rosenow et al. 2017; Howlett and Mukherjee 2018). From that standpoint, scholars treat actors’ values and preferences, State’s capacity, regulation, spaces and administrative structures as independent variables of the policy design (Considine et  al. 2014; Araral 2014; Chindarkar et  al. 2017). Political economy and comparative historical analysis are also conveyed to explain policy change (Hall 1993). However the relationship between governance and policy design remains indeterminate inasmuch as a governance mode is actually defined by a government’s preferences for an instruments mix, which is allegedly driven by a governance mode. Actually this model is more akin to bridging theory and practice at a micro-level (through program design) than to producing a general explanation of policy outcomes based on policy design. 3.4  Policy Design as Institutionalization The fourth model defines policy design as a web of institutional interactions between actors, instruments and environment. Here causation is conceived as a series of dispositional explanations of how a policy outcome is produced in an open system by INUS complexes; evaluation is carried out through the assessment of causal forces made out of the interplays between actors’ values, instruments mixes and the public administration; and intervention rests upon within-case studies and small-n comparison for confirming or disconfirming purposes. Policy instruments are the fingerprints of the choices made by a government to achieve a policy aim, which are detectable but not directly observable. From this realist approach, the taxonomy of instruments by the State’s resources of nodality, authority, treasure and organization can be used to appraise different kinds of mechanisms (for instance setting control or ensuring compliance through authority instruments) involving different kinds of actors (for instance rule makers and rule enforcers). Policy design as institutionalization reckons that the decisions made by actors are constrained by their material and ideational environment. A

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policy results from a combination of choices regarding goal setting, formulation and implementation “machines”, and the environment, with each one of these entities being independent from one another and unrelated sequentially (Linder and Peters 1987, 471). The complexity of such combinations increases when it comes to explain a mix of policy instruments, which is not only constrained by the political system, the organizational setting of State actors and the problem situations, but is also guided by subjective factors intervening between the context and the choice, such as meaning interpretation or utility perceptions (Linder and Peters 1989). The institutionalization model links policy objectives and outcomes through mechanisms of formulation, implementation and responses to contingency (Fig. 2.5). Each part of the system is conceived as a mechanism exerting causal forces on the decisions made by the actors involved, thus responsible for the policy outcome. Policy design is set in motion by the adoption of policy goals, which means the agenda setting is understood as a proper activity related with policy formulation and implementation in a changing environment. Further, attention is called on the dynamics articulating these four dimensions and the feedback effects of systemic interplays, as opposed to a linear pathway of decision-making. Formulation and implementation are causal forces that follow different logics, whose combination influences the bounded rationality of State actors and publics. Consequently, each dimension is to be understood as a complex entity instead of a set of variables to control for. This model stems from the question about how we can address policy problems through design. The argument is threefold: design is a way to think systematically about what makes a “good” policy, it facilitates policy learning and evaluation, and it has practical and theoretical dimensions. From that standpoint, policy design is a political process that “involves attempts to integrate understandings of the problems being addressed with some ideas of the instruments used for intervention, and the values that are being sought through the policy” (Peters 2018, 5). It is mainly “redesign”, which means a new policy is often based on former versions or is a follow­up of existing patterns of interactions between actors, instruments and {Goal}*{Formulation machine}*{Implementation machine}*{Environment}

Fig. 2.5  The policy design as institutionalization model. (Source: Adapted from Linder and Peters 1987, 470)

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environment. Yet unlike other forms of design, such as architecture or engineering, it involves humans, values and the conflicts thereof. It also implies targeting and modulation according to people’s needs and government’s capacities. According to this model, there are different types of policy design ranked on a continuum leading from non-design (which means the policy lacks the minimum government’s consciousness that would make it a consistent answer to a problem) to full design (which means the government intends to have it all under control). Along this continuum policy design should be differentiated from program design, and its ideological and political dimensions should be underlined. There is also a substantive difference between policy design by transfer and innovation or between accidental and experimental design. The institutionalization model pays a special attention to the definition of policy problems, as a political process rather than a technical exercise. The “problem of policy problems” (Peters 2018, 35–55), when defined in terms of policy area, is twofold. On one hand they are subject to internal variations (for instance universal access to education has a different meaning whether it applies to primary or higher education). On the other hand they are often linked across policy areas (for instance food security is related to agriculture and trade policies). Hence the necessity to classify them according to their substantive nature, their structure, their degree of technical and political complexity (etc.), rather than their sectorial anchorage. This raises questions about the differences between difficult, complex and wicked problems (idem 2018, 60–79). Wicked problems are defined by their complexity, the uncertainty of the solutions and the disagreement they raise among actors. They turn into wicked problems when adding the fact that no central authority is responsible for their solution, time is running, or if the same actor which is responsible for the problem owns the key to its resolution (like oil producers are key actors of the post-carbon energy transition). Whatever the degree of complexity, these problems are addressed through the selection of policy instruments (idem 2018, 90–110), however the institutionalization model differs from the instrumentation one by reckoning that policy instruments embody more than optimum solutions resulting from instrumental rationality. Policy instruments features can be gathered in two sets of choice criteria which are, on one hand, the traditional characteristics of complexity, visibility, adaptability, intrusiveness, cost, reliance on market, chances of failure or targeting precision

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and, on the other hand, more recently identified characteristics like universal/categorical, stocks/flows, self-administrated/administrated, collaborative and automatic. Rather than selecting rationally these instruments, a government has to cope with their intrinsic nature of hybrid, highly political and value-driven tools. Not only instruments choice is often path-­ dependent and highly constrained by past individual behaviors and bounded rationality, but instruments evaluation is also subject to different interpretations (or framing) regarding their economic, political, administrative and ethical characteristics. A major challenge for policy-makers is to avoid the biases of “unconscious design” (Linder and Peters 1990a, 305; 1991, 127) due to prejudices, evaluative assumptions, instruments mismatch, etc. In that context, the model constitutes a heuristic tool to foster “conscious” decision-­ making (Linder and Peters 1991, 130) by organizing actors and instruments before assessing their combinations according to substantive criteria related with the policy problem and context. It rests on four premises including the separation of value and feasibility, the separation of design and decision-making, the enumeration problem in terms of methods and conditions, and the appraisal problem (Linder and Peters 1990a, 307–308). The most salient issues in this realist approach to policy design deal with the governance interplays resulting from the transformation of the State and the relationships between the government, non-State actors, international organizations and local communities (Salamon 2000; Pierre and Peters 2000; Olsen 2010; Pierre 2012). From that standpoint a policy essentially results from choices following the logic of appropriateness theorized by sociological neo-institutionalism (March and Olsen 2006). Scholars intend to explain policy implementation in actual situations, so instrumentation is essentially contingent (Bresser and Klok 1988; Linder and Peters 1991). They also treat policy instruments as institutions enjoying autonomy from individual and collective actors (Linder and Peters 1990b; Peters 2000; Lascoumes and Le Galès 2007; Le Galès 2010). Recent research interested in institutional and policy change reckons that it is produced by complex causal mechanisms articulating ideas, interests and institutions that cannot be treated as independent variables (Fontaine et al. 2018). Therefore scholars aim at building and testing middle-range theories as roadmaps, in order for practitioners to solve increasingly complex problems after improving their understanding of the relationships between actors, instruments and environment (Peters 2018).

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4   Conclusion: Comparative Policy Design In a nutshell, the scholarship on policy making over the past three decades has produced multiple theories concealing huge discrepancies on the very nature of policy design. This does not cast doubt on the analytical value of the policy design framework, but to fulfill the objective of comparative policy analysis, scholars engaged in this debate should align their methods with their scientific and philosophical ontologies. A safe way to proceed is to relate substantial theories with the four methodologies defined by philosophical and scientific ontologies: neo-positivism, realism, analyticism and reflexivity (Jackson 2016). Then it becomes easier to address potential inconsistencies between the aims and means of the research design. Drawing on Peters (2018), this chapter has identified four different models of causation, intervention, evaluation and instrumentation, based on four different methodologies. These methodologies act as scientific paradigms for their incommensurability (Kuhn 2012), which explains why the discussion on policy design theories and methods is so wearisome and why scholars’ arguments often fall on deaf ears through dedicated journals. Although a methodology does not command a specific type of substantial theories and methods, our state of the art points toward a notorious consistency between each methodology and substantial theories of the policy design, which has consequences on methods selection. This symmetry may come from “sociological developments” (Jackson 2016, 203) such as the preferences by editorial committees and school boards. But it may also come from the very process of policy design in theory and practice. In particular, there is a symmetry worth noticing between the differences in methodologies and the differences in the treatment of substantive issues like the role of ideas in policy design. On one hand, each methodology supports a different theory of the politics of the policy design. Along the spectrum that goes from the de-politicization to the hyper-­politicization of the policy design, sociological factors are as important as the theoretical and the methodological ones. Ideas are essential in monist ontologies but theories grounded in analyticism are actually based on ideas, as expressed by the very concept of ideal-type, while theories grounded in reflexivity advocate for a politicization of policy design for the sake of democracy. Conversely, ideas are clearly a secondary issue for dualist ontologies but while theories grounded in neo-positivism share a common lack of interest for ideas, those grounded in realism reckon the role of ideas as it is supported by institutional systems.

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On the other hand, each methodology addresses the role of policy instruments in different ways. Neo-positivists treat policy instruments as substantive tools chosen rationally by the government, so they tend to conceive policy design as instruments constituency, in accordance with rational choice theories. Realists treat them as the products of causal powers acting with a certain degree of independence, so they tend to underline a logic of appropriateness rather than a logic of consequences in the policy design. Analyticists treat policy instruments as cognitive phenomena expressing the divergence between actors’ representations of policy aims and means, so they tend to see policy design as an exercise of social construction of aims, means and target groups. Eventually reflexivists treat them as instruments of domination used by a government to establish their authority and perpetuate the status quo ante, so they see policy design as an emancipatory activity, in compliance with argumentative theories like the critical theory.

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CHAPTER 3

A Realist Approach to Policy Design

1   Introduction: Aligning Our Methods With Realism We have seen in Chap. 2 that the realist approach to policy design focused first and foremost on the interplays between goals, actors and context in the definition of the instruments mix featuring a policy style. The realist approach to policy design is ontologically aligned with small-n comparison when it aims at explaining how the adoption of a policy goal is causally linked to a policy outcome, because it requires to identify a causal mechanism in the policy design process. In social sciences realism is sometimes mistakenly presented as a third way between positivism and interpretivism (Marsh and Furlong 2010, 186) or as a synonym of constructivism (Parsons 2010; Dowding 2016, 27). Nevertheless “constructivism” and “interpretivism” are catch-all concepts that conflate different questions in epistemological, theoretical and methodological debates. As a matter of fact conceiving the world as a social construction (Bobrow and Dryzek 1987; Schneider and Ingram 1997; Fischer 2009) is different from conceiving our knowledge about the world as a social construction whose objects are structures and mechanisms that generate phenomena (Bhaskar 1978, 15). This stems from the difference between the intransitive and the transitive dimensions of knowledge, that is to say between the physical processes and social phenomena in the world on one hand, and the discourses and © The Author(s) 2020 G. Fontaine et al., The Politics of Public Accountability, International Series on Public Policy, https://doi.org/10.1007/978-3-030-28995-9_3

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theories about the world on the other hand (Sayer 2000, 11). This difference is caught by the “stratified ontology” (Sayer 2000, 12) of realism, which is based on the distinction between the real, the actual and the empirical. The real refers to the realm of objects (whatever exists), the actual refers to the realm of activities (what happens if causal powers are activated) and the empirical refers to the realm of experience (what we observe in the world). Consequently realism is better understood as a methodology combining dualism with transfactualism, as opposed to neo-positivism, analyticism and reflexivism (Jackson 2016, 41). The premise here is twofold. First, realists concur with neopositivists in that causal explanations of the world are possible. In this they depart from analyticists and reflexivists, to whom only interpretations (as opposed to explanations) of social processes like public policies can be produced because anything that can be said about them is affected by our being part of the world we study. Second, yet realists concur with reflexivists in that social processes can be understood through detectable though non-directly observable phenomena. In this they depart from neo-positivists and analyticists, to whom empirical evidence in a scientific research can only proceed from directly observed phenomena. We refer to realism rather than to “critical” realism, thus following the original statement of a realist scientific endeavor (Bhaskar 1978). The “critical” realist argument against Hume’s “empirical realism” is that the world is an open system where regularities are more the exception than the rule, and our knowledge about the world cannot be reduced to atomistic events (Sayer 1992; Archer et al. 1998). Now this argument can be sustained without assuming the epistemology of historical materialism or the Marxist theory of social classes (Pawson 2016). The question whether social scientists should assume a critical attitude toward their subject and object (Sayer 2000, 158) is a normative issue that refers to sociological factors, like the constitution of and the production by epistemic communities. Critical theory might as well be assumed by reflexivists and analyticists, so it is not exclusive of a realist methodology. So what are the methodological implications of realism for the policy design framework? The conception of causality and causation1 predicated by an ontology guides the choice of quantitative and qualitative methods 1  Causality is a relationship between cause and effect, and causation is the act of causing something.

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in a research design. This means some methods aimed at producing causal explanations are more consistent with realism than others, although realism does not command the use of any particular method. When consistently aligned with realism, these methods are based on a transfactual analysis and they deal with causal forces rather than covariance or ideal types. For that purpose, a research design combining case study and small­n comparison techniques (such as process tracing and qualitative comparative analysis (QCA)) (Berg-Schlosser 2012; Schneider and Rohlfing 2013; Beach 2018) seems more accurate than a research design combining largen comparison and within-case studies techniques (like standard linear ­ regressions and quasi-experiments) (Seawright and Gerring 2008; Seawright 2016). Section 2 is dedicated to unpack the causal mechanism of a policy outcome in policy design. It starts with defining causality as necessity and causal mechanisms as causal forces, then it proceeds with optimizing case selection for small-n comparison. Section 3 explains how to conduct a cross-case comparison of this causal mechanism. It starts presenting the basics of set-theoretic research design, then it explains how the Bayesian logic of likelihood can be utilized to assess empirical evidence, and it proposes a template for comparative policy design.

2   Unpacking the Causal Mechanism of a Policy Outcome 2.1  Causality as Necessity A public policy meets individually the “intrinsic condition for closure” (Sayer 1992, 122) so that there must be no change in the object (like an instruments mix) if its causal forces are to operate consistently. For instance, if resource nationalism is a cause of public accountability deficit, there must be a causal mechanism at work which should always be the same, regardless of the country and the government. Yet a public policy is an open system which lacks the “constancy extrinsic conditions” (Bhaskar 1978, 67) that would allow for stable empirical relationships. The context affects the way causal forces produce their effects, which makes policy outcomes irregular and hardly predictable, especially in a deep or fast changing context. Furthermore several mechanisms may be contingently related to one another, so that the same mechanism can produce different

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effects and different mechanisms can produce the same effect. Therefore a major issue raised by the intrinsic conditions of policy design for closure concerns the delimitation of the policy area, be it in terms of scope (the substantive policy area), geographic scale (the territorial level of public administration) and time sequencing (the duration and order of policy programs). For a neo-positivist a causal explanation is predictive by definition (Dowding 2016, 79) so a “predictive causal explanation” is a tautology. Conversely for a realist causal explanations may or may not be predictive, according to the meaning of causality. For them, causality does not lay in directly observable phenomena but in the causal powers and liabilities of objects, relations, events (etc.) which act as mechanisms between these events (Sayer 1992, 104). Causal powers are detectable but not directly observable, hence their transfactual nature. Therefore building and testing a realist theory of causation is not about finding a regularity between two discrete entities but about assessing how they are related to one another (Sayer 1992, 105). This marks the difference between looking for a “necessary cause” (as in: “if X:Y then there is a necessary causal force at work in between”) and looking for a “necessary condition” (as in: “if X:Y then X is a necessary condition for Y”). This difference lays in the necessary or contingent relationships between structures, events and the mechanism at work in between: “the relationship between objects and causal powers is necessary; the relationship between these and their conditions is contingent” (Sayer 1992, 108). The attributes of a causal mechanism are necessary but its actual effect is contingent, which means this mechanism exists even when it does not produce an outcome, it can be inactive until a trigger kicks in. Here “contingency” means that two related entities enjoy an independent status, whereas “necessity” means their existence relies on their mutual status. This definition of necessity relies on a deterministic logic of causation as opposed to the probabilistic one stated by neo-positivists. Both logics of causation call for different research designs, aligned with different methodologies, for instance to explain the causal relationship between a nationalist oil policy and a public accountability deficit. A neo-positivist approach would seek for a regularity across as many cases as possible in order to control for as many variables as possible and minimize error. On the contrary, a realist approach would focus on a limited number of cases or even on a single case featuring the attributes of oil nationalism and public accountability deficit, in order to disclose the causal forces at work in this

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relationship. It would define the attributes of the causal mechanism responsible for this particular policy outcome before looking for empirical evidence to confirm or disconfirm this theoretical mechanism. While assessing regularity implies conducting an extensive research design (focused on a few variables across as many cases as possible), assessing necessity commands an intensive one (providing a detailed account of a few cases selected for their significance). Extensive research deals with causality as a formal problem of similarity, which leads to ask about what conditions are theoretically necessary to trigger a process. Intensive research treats causality as a substantial problem of connection, which leads to wonder what it is about an entity that produces a causal power. While extensive research produces predictive theories of causation, that is to say generalizations of causality or ideal types without explanatory penetration, intensive research produces non-predictive explanations, that is to say causal explanations or interpretations of the production of specific outcomes (Sayer 2000, 21). Consequently extensive research may produce “causal laws” or general theories, whereas intensive research seeks to produce “instrumentalist laws” or middle-range theories (Sayer 1992, 127–128). These theories of causation fulfill different functions. General theories describe regularities so they are limited to closed systems; but they do not identify causal forces so they are not explanatory in a deterministic sense. Only middle-range theories describe how the qualitative nature of a social phenomenon varies according to the context. The difference between intensive and extensive research designs partly overlaps the dilemma between quantitative and qualitative methods even though both may combine these methods. The underpinning logic of a predictive explanation is probabilistic, which is why prediction can only be achieved through quantitative methods and formal modelization (Ostrom 2011). Conversely a non-predictive causal explanation does not lean on a probabilistic logic insofar as it consists in defining the intrinsic elements of the causal process leading to an outcome (Beach and Pedersen 2016). Consequently intensive research is akin to case study analysis and small-n comparison, unlike extensive research which requires large-n comparison occasionally completed by case-studies. In either case multi-methods are useful for exploratory purposes in theory building, or for confirming or disconfirming purposes in theory testing. But only intensive research may be interested in deep within-case studies of non-representative processes. Eventually this division of labor refers to different approaches to the issue of theoretical generalization and different appreciations regarding

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the number of cases or observations deemed sufficient to build and test a causal explanation or interpretation. Drawing on natural sciences, the neo-­ positivist definition of generalization refers either to variant theories (for empirical generalizations) or invariant ones (for law-like generalizations) (Dowding 2016, 62–63). In any case, the premise behind this definition it that the external validity of a causal relationship depends on the correlation between an independent and a dependent variable, so that the higher the number of observations, the better for the theory. Assessing the covariance between X and Y requires multiplying observations to calculate the probability that a variation in X causes a variation in Y or that in absence of a variation in X there is no variation in Y. From that standpoint, qualitative methods are inaccurate to establish or test a causal relationship so they are, at best, a complement to statistics. For instance scholars may use process tracing as a secondary technique to shed light on a particular aspect of probabilistic models built on econometrics (Seawright 2016; Collier 2011). Even when they reckon case studies have some probatory value (Mahoney 2001; Goertz and Starr 2003; Goertz and Mahoney 2012) their search for sufficient and necessary conditions still requires the kind of cross-case comparison driven by a probabilistic logic of causation. For instance they may combine process tracing with comparative historical analysis and political economy (Falleti 2010; Mahoney 2012; Hall 2012). For realists, if a causal explanation or theory is to travel across cases, it is because it sheds light on the necessary liabilities of the causal mechanism that produces an outcome. This depends on the available evidence proving that the causal forces are actually connected within a particular context (Beach and Pedersen 2016), so that the higher the internal validity, the better for the research, even though its conclusions may just allow to build or test a middle-range theory. Assessing a causal process between a trigger (T) and an outcome (O)2 implies looking within a case the way a series of entities (organizations, actors, events, etc.) are connected together and interact with the context so that T triggers a process leading to an outcome O1 in a context S1, or that this mechanism deviates or breaks out in a context S2 and produces a different outcome O2. Therefore instead of seeking for a probabilistic relationship between independent and 2  We refer to T and O instead of X and Y, in order to avoid any confusion with the probabilistic language of independent, dependent and intervening variables used in neo-positivist process tracing.

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­ ependent variables, cross-case comparison aims at confirming or discond firming a deterministic causal relationship. 2.2  Causal Mechanisms as Causal Forces Causal mechanisms lie at the core of process tracing methods, which might otherwise consist in a descriptive exercise to account for a pathway or to build up a narrative on a series of events (Beach 2016). Whether the process is political, economical, social or even psychological, whether the agent of causation is individual or collective, whether the time frame refers to long-lasting or instantaneous, unique or regular events, this does not affect the fact that all entities or parts of a causal mechanism are effectively related in a way that has T producing O. However the concept of mechanism is a polysemic one, whose definition can vary according to the process under scrutiny (be it a historical event, a political decision or a diplomatic negotiation). In the broadest sense it describes a causal relationship linking an explanans X to an explandum Y (Gerring 2007, 166). In a narrower sense it is but one modality of causation among others, such as temporal and spatial contiguity, causal chains and process dynamics, causal combinations or configurations (Blatter and Haverland 2012, 91–92). It can be theorized as parts of a narrative (Ruback 2010; Crasnow 2017) or an analytical process (Beach 2013), as a theoretical issue (Paquet and Broschek 2017), an ontological one (Gerring 2007) or a methodological one (Mahoney 2016). Mechanisms also uncover different meanings according to scholars’ philosophical and scientific ontology. For neo-positivists and analyticists, they are part of an on-going process of theory building and testing which provides either “useful pieces of a theory” (Stinchcombe 1991, 367) or partial explanations or intermediate paths to develop a general theory (Hall 2012). As such a mechanism is a useful way to make sense of the data but needs being formalized into a model if it is to become part of a causal explanation (Dowding 2016, 94). For realists, they are “elementary building blocks of middle-range theories” which differ from nomothetic theories because they are “unobserved analytical constructs” playing out to articulate the micro- and the macro-levels of social action (Hedström and Swedberg 1998). These conceptual differences derive in different procedures when it comes to explain a causal process. For neo-positivists and analyticists, a causal mechanism is a set of unstructured “intervening variables” (King

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et al. 1994) in which variables are a representation of directly observable phenomena. Therefore “opening the blackbox” through process tracing consists in testing a theory based on a probabilistic model, by explaining either how the cogs and wheels work in a typical case, or how a disruptive factor works in a deviant case (Brady et al. 2010; Falleti and Lynch 2009). However for realists and reflexivists, a causal mechanism is a set of entities engaged in causal activities and related to endogenous and exogenous factors (Machamer 2004), “a theory of a system of interlocking parts that transmits causal forces” (Beach and Pedersen 2013:29). As such a mechanism is made out of entities that are empirically observable manifestations of something that is detectable but not directly observable (a causal force). Therefore, “opening the blackbox” consists in identifying “causal process observations” (George and Bennett 2005) or expected empirical observations that later need to be turned into evidence (Bennett and Checkel 2015; Bennett 2015) to reveal the causal mechanism’s structure, hierarchy and sequencing (Hedström and Ylikoski 2010). The very fact that we believe or know something about a causal relationship even before engaging in process tracing implies that the research aims at building or testing a theoretical causal mechanism and that, at least, one other method has been utilized to formulate our hypothesis. Process tracing is a method, not a theoretical framework, so there is no reason to reduce it to an agent-based model (but see Hedström and Swedberg 1998; Hedström and Ylikoski 2010). Agent-based modeling may be effective to explain decision-making, but it is of limited value to provide a full-range explanation of the complexity at stake in an implementation gap or a policy change. In fact process tracing can deal with different kinds of processes and different theories. To give but two examples, it can apply to an institutional explanation of a “realized” process or it can apply to an agent-based explanation of an “anticipated” process (Rohlfing 2014). While the former may involve multi-level interactions, like the international and the national context of fiscal policies in the European Union, the later may refer to expected interactions or patterns of behavior, such as those predicted by the democratic peace theory (George and Bennett 2005). The purpose of realist process tracing is twofold: it consists in the identification of the entities that make up a mechanism (the substance) and the activities these entities engage in (the process). The problem of causal mechanism theorization can be summarized as follows: we believe with a certain degree of confidence that an event triggered a process leading to

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an outcome, but we don’t know why. The notion of trigger is more accurate here than that of independent variable because it can either refer to a single or a reiterative process. Regardless of the intrinsic nature of a causal mechanism, it needs being activated in order to produce the expected outcome, hence the need to identifying the initial event or the event from which a causal process follows. This event can be either endogenous or exogenous to the process. For instance in the case of oil nationalism causing a deficit in public accountability, it can be the election of a nationalist government or the adoption of a policy aim by this government (which is an endogenous cause of the policy design as it is directly related to a government adopting policy aims), or it can be the evolution of oil prices on world markets (which is an exogenous cause of the policy design as it escapes to a government’s control). No matter what criteria are used to coin this event as the trigger, there is always a preceding event which is likely to be part of the causal process, even before what historians call “critical junctures” in the path dependence theory (Capoccia and Kelemen 2007). That being said, process tracing is essentially prospective as it stands as a method to explain a causal relationship between a trigger and an outcome. Whenever seeking an explanation to the origin of a trigger (as in: “Why did X happen?”) the theoretical causal mechanism would consider a particular event as the trigger (W) of a different process, so that W triggered the process P1 leading to X, which triggered the process P2 leading to Y. The decision is up to how deep and precise the causal explanation is expected to be: the more extensive the process, the more empirical data will be needed to assess a causal mechanism. Anyway if process tracing consists in analyzing the causal forces at work in a relationship between a trigger T and an outcome O, then it is necessary to consider both T and O as parts of the process. Consequently it is of little interest conducting an “intensive” process tracing (Falleti 2016) that would only focus on what happens after a trigger has been activated or before an outcome has been produced. Excluding the trigger or the outcome from a process tracing exercise could only mean one process is nested in another one. This might produce an insightful knowledge on the entities and activities under scrutiny but it would not allow to draw any conclusion beyond speculation on the causal process as a whole. For that matter it is a major limitation of the use of the path dependence theory in policy design, in spite of the irreplaceable contribution of historical institutionalism to the analysis of causal complexity through

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framing and detailed analysis of rare events (Bennett and Eldman 2006). Based on long-term process tracing, this theory excels at explaining policy stability after critical junctures leading to a third-order or a paradigmatic policy change (Hall 1993; Kern et al. 2014). But it fails to produce accurate explanations of short term and medium term change due to policy learning (or first and second order change) (Kay 2005; Howlett and Rayner 2006). Likewise, it makes little sense separating a mechanism from its context (but see Falleti and Lynch 2009), since process tracing precisely consists in integrating the causal mechanism piecemeal entities and the context into a single causal process. Realist process tracing is neither a descriptive exercise of how a theoretical mechanism should work all other things equal, nor a prescriptive one to convert a case study into an ideal-type or a model. It is about explaining how a set of entities work in context, how each part and the whole of them interact with a social context or what contextual factors prevent them from producing an expected effect (Astbury and Leeuw 2010). This does not mean all contextual elements are relevant for the causal mechanism under scrutiny, nor that these should be controlled for as independent variables. On the contrary, the incidence of the context on a policy design should be based on the very same deterministic logic of causality that guides the theorization of a causal mechanism. For instance in the case of oil nationalism causing a deficit of public accountability, the evolution of oil prices on world markets is a contextual element that needs being integrated to the causal mechanism insofar as it has a direct incidence on this particular policy design. To do so, we should look for pieces of evidence of oil prices being taken into account by the government along the process leading from the adoption of nationalist aims to a public accountability deficit in the oil policy. Accordingly, contextual factors such as the relationships between the executive and the legislative powers, the organization of the civil society, the design of other substantive policies (etc.) can be integrated to the causal process through a systematic inquiry of how they are taken into account by the government and how they reflect on the government’s decisions during the process. 2.3  Case Selection for Small-n Comparison Process tracing is not only a method of gathering evidence for a within-­ case study (Gerring 2007), but it can also be used in cross-case c­ omparison

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as part of a set-theoretic multi-method research design (Rohlfing and Schneider 2016). Cross-case comparison is the only way to provide a case study with some degree of generalization (Peters 2013) but, as already mentioned, this means two different things from a probabilistic or a deterministic standpoint. On one hand, the probabilistic logic produces theories of causation based on mean causal effects, general trends and symmetric causation, which commands extensive or variable-centered research designs for large-n comparison. On the other hand, the deterministic logic supports theories of causation based on differences in kind, necessity claims and asymmetric causation, which commands intensive or case-based research designs for small-n comparison and within-case studies. Yet the combination of both logics lies at the heart of a multi-method research design (Rohlfing and Schneider 2016; Lorentzen et  al. 2017; Beach 2018) so it requires careful methodological alignment when it comes to the conceptualization of causal conditions (necessity and sufficiency), the status of a case set membership and the selection of techniques of measurement. As in the “epistemic theory of causality” in health sciences (Russo and Williamson 2007), realist social scientists reckon a difference in kind between probabilistic and mechanistic evidence, but they use them both to produce a satisfactory explanation of a causal relationship between a policy aim (T) and a policy outcome (O). To be sure, the “mechanistic” evidence may consist in both qualitative and quantitative data but the difference lays between two kinds of evidence, not between two kinds of evidence-gathering methods (McKay Illari 2011; Marchionni and Reijula 2018). Case selection for process tracing takes two intermediary steps. First it requires operationalizing T and O to answer the question: When can we assure that T and O are present in a case? This can be done by elaborating a truth table for causal homogeneity, based on a crisp-set QCA in which all the possible cases are listed and the attributes of T and O are assessed for each possible case. These attributes are coded X1∗Xn if we wish to include only cases showing a combination of X1 AND Xn, or X1 + Xn if we wish to broaden the population of cases showing either X1 OR Xn. For instance to determine if a case fits in the category of “oil nationalism” we can scan a country’s oil sector regulation to see if the national oil company receives a special treatment (as compared with multinational companies) or if the contractual regime favors state-led investments over market rules. Likewise, to determine if a case fits in the category of “public accountability deficit” we can use surveys on democratic governance to see if the

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government lacks the support of public opinion or if there is a perception of opacity by citizens. The second intermediary step consists in building up a typology of cases for consistency, based on a fuzzy-set QCA in which all cases are distributed according to their set membership (Schneider and Rohlfing 2013). This typology provides a conceptual definition of each case as “a case of”, so that the selection can rely on a systematic assessment of the presence or absence of the trigger and the outcome. At this stage of the research we are not supposed to know whether a case provides enough evidence to confirm the hypothesis or not. However through fs-QCA we can spare some precious time and avoid the effects of soaking and poking by narrowing the scope of case selection. Needless to mention that this empirical utilization of QCA techniques has little to do with the neo-­ positivist approach of variables control and theory falsification. Table 3.1 presents a typology of cases based on set-membership for consistency. A typical case is defined by the presence of both the trigger and the outcome (T∗O). A deviant case is positive on the trigger but negative on the outcome (T∗¬O). An individually irrelevant case is one where neither the trigger nor the outcome is present (¬T∗¬O). An inconsistent case is one where the outcome is present but not the trigger (¬T∗O). All other things equal, if the research hypothesis is sensible we should expect a majority of cases to fall either in the “typical” or in the “individually irrelevant” categories, a few ones in the “deviant” category and a residual minority in the “inconsistent” category. This means, for instance, that in most cases nationalist oil policies co-exist with a deficit of public accountability and where there is no nationalist oil policy there is no deficit of public accountability. Eventually if all cases were to fall in the “typical” category the theory would almost certainly be trivial and if all of them were to fall in the “inconsistent” category, the hypothesis would almost certainly be meaningless. This could mean, for instance, that a lack of Table 3.1  A typology of cases for consistency Outcome

Trigger

+ −

+



Typical Deviant

Inconsistent Individually irrelevant

Source: Elaborated by the authors, adapted from Schneider and Rohlfing (2013)

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public accountability is an intrinsic feature of a nationalist oil policy, or that nationalism has nothing to do with a public accountability deficit. Anyway a typical case is best for theory building and testing because it presents the most likely situation where a detectable though non-­ observable causal mechanism connecting T to O actually exists (Beach and Rohlfing 2015). Deviant cases are also useful for theory testing because they allow to revise and precise the initial hypothesis. Individually irrelevant cases are out of the scope of process tracing, since the method does not deal with symmetry in causality (that is to say, the absence of a causal factor is not considered as a cause of the absence of an outcome). Inconsistent cases are useful insofar as they can reveal inconsistencies in the main hypothesis, due to spurious or omitted variables, hence leading to a new process theorization. The following section provides a template for comparative policy design based on a realist approach to the problems of causation, causal mechanism definition and case selection explained above.

3   Policy Design in Cross-case Comparison 3.1  A Set-Theoretic Research Design In the institutional model of policy design, a policy results from the interplays between goals adoption, the formulation machine, the implementation machine and the context, which define the instruments mix favored by a government. Policy design is a process linking the adoption of aims by a government to the production of an outcome. But unlike the policy cycle framework, it is neither about explaining the process leading to the adoption of these aims, nor about evaluating the impact of those outcomes. Taking into consideration these upstream and downstream issues may certainly contribute to improve a policy design, but it is not part of it. This model can be adapted to a short-term cycle or a sequence of the decision-making process regarding a substantive policy, which is described in Fig. 3.1. The theoretical process rolls out as follows. The agenda setting (T) triggers a three-part causal mechanism (A, B, C) producing a policy outcome (O). Initially the government adopts policy aims through the agenda setting (T), then it defines the means to fulfill them through the policy formulation (A), then it coordinates this policy with other existing policy areas through institutional change (B), then it processes non-State actors’

Theorization

G. FONTAINE ET AL.

Agenda setting

Policy formulation

Cross-sectorial coordination

Political interplays

Policy outcome

Operationalization

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New policy aims claimed by government

Change in sectorial policy

Change in institutional system

Implementation style in Statesociety relationships

Public account of policy outcome

Fig. 3.1  A causal mechanism in policy design. (Source: Elaborated by the authors)

demands regarding the implemented policy through political interplays (C), then it accounts for the policy outcomes at one time or another (O). Confirming the existence of this causal mechanism requires to observe the government claiming new policy aims in T, a change in the policy area in A and in the institutional system in B, a preferred implementation style in State-society relationships in C and a public account of the policy outcome in O.  These parts are causally related (H  =  T:A:B:C:O) and the whole process is the sum of the trigger, the outcome and the mechanism (H  =  hT∗hA∗hB∗hC∗hO). This means the confirmation of the theoretical process depends on the confirmation of its weakest part (Beach and Pedersen 2013, 106). Furthermore any potential loop effect or back and forth movement affecting the same policy is a process within the process, thus a case study by itself. Eventually it can take three different pathways leading to confirm the existence of a causal mechanism, disconfirm it or to identify factors of equifinality (Beach and Rohlfing 2015, 11). Once a theoretical causal mechanism of policy design has been built in and operationalized, we can proceed with defining the expected empirical observations we will look for if the hypothesis stands. 3.2  Policy Instruments as Expected Empirical Observations The evidence assessment in process tracing is a two-tier analysis. First a main hypothesis (h) and an alternate hypothesis (¬h) are formulated for each part of the process, including the trigger, the outcome and the causal mechanism in-between. Unlike the main hypotheses, the alternate

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­ ypotheses are not bound together by a causal relationship because causalh ity here is not symmetric (that is to say, in absence of T we do not know anything about O). They are “empirical counterfactual” elements (Rohlfing 2014) for each individual entity of the causal process. Further, an alternate hypothesis is not a competing hypothesis against which the causal mechanism should be tested. It just conflates all other possible hypotheses that may disconfirm the theoretical causal mechanism. In other words, only h can be confirmed. The logic here is comparable to that of a court trial, where the defendant may leave the court either guilty of charge or innocent, without the judge saying anything about other possible suspects. Should the main hypothesis be disconfirmed, it would be discarded or reformulated but the alternate hypothesis would remain indeterminate (Beach and Pedersen 2013; Bennett and Checkel 2015). This departs from the logic of a medical or pharmaceutical experiment, akin to neo-­ positivist and analyticist process tracing, where each possible hypothesis is expected to be treated with the same prior degree of confidence before being tested against available evidence (Humphreys and Jacobs 2015; Fairfield and Charman 2017). Second a series of empirical tests are designed to identify the expected empirical observations considering H and assess their potential probatory value. An expected empirical observation refers to what kind of evidence is needed to confirm h, so that the result would be disconfirming if no evidence was found or if evidence of ¬h was found. As already mentioned in Chap. 2, the instruments of nodality, authority, treasure and organization combined into a policy mix provide clear-cut evidence of a government’s intentions and actions (Hood 1986, 115). The rationale here is that these instruments constitute an INUS condition for a policy to actually exist, regardless of its inputs and outputs. Policy instruments bear fingerprints of whatever can be said about a policy, therefore the entities entering in activity to produce a policy outcome can be empirically observable through the policy mix. Table 3.2 presents a typology of these expected empirical observations for each part of the causal process at stake in a policy design, if our main hypothesis stands. If hT stands, explicit claims by the government should be observed in its program (PT1), in the constitutive regulation (PT2), in the development model (PT3) and in the design of the State apparatus (PT4). If hA stands, a change in the policy should be seen at a sectorial level in planning (PA1), regulation (PA2), budget allocation (PA3) and administration (PA4). If hB

New policy aim claimed by government (hT) Explicit claims in the government’s program (PT1) Explicit claims by government in constitutive regulation (PT2) Explicit claims by government in the development model (PT3) Explicit claims by government in State apparatus design (PT4)

Source: Elaborated by the authors

Organization instruments

Treasure instruments

Authority instruments

Nodality instruments

Hypothesis

Change in policy area administration (PA4)

Change in policy area budget allocation (PA3)

Change in policy area regulation (PA2)

Change in policy area planning (PA1)

Change in sectorial policy (hA)

Implementation style in State-society relationships (hC) Place of non-State actors in incumbent’s statements (PC1) Place of non-State actors in legislative process (PC2)

Change in cross-­ sectorial administration (PB4)

Place of non-State actors in local governments (PC4)

Change in the Place of non-State cross-sectorial budget actors in budget allocation (PB3) execution (PC3)

Change in institutional system (hB) Change in the cross-sectorial planning (PB1) Change in the cross-sectorial regulation (PB2)

Table 3.2  Expected empirical observations in a policy design process

Autonomy by balance and control agencies (PO4)

Financial assessments by government (PO3)

Public account of policy outcome (hO) Access to information system (PO1) Respect of due process by State agencies (PO2)

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stands, a change in the institutional system at a cross-sectorial level should be observed in planning (PB1), regulation (PB2), budget allocation (PB3) and administration (PB4). If hC stands, the implementation style favored by a government in its political interplays with non-State actors should be expressed in the government’s statements (PC1), in the legislative process (PC2), in the State budget execution (PC3) and in  local governments (PC4). Eventually if hO stands, the policy outcome for public accountability should be observed in the access to the information system by non-­ State actors (PO1), the degree of due process achieved by State agencies (PO2), the availability of timely financial assessments made by the government (PO3), and the degree of balance and control agencies’ autonomy (PO4). Based on these expected empirical observations, the data collection on the policy design can be conducted in a systematic fashion in order to facilitate the evidence assessment for confirming or disconfirming purpose. 3.3  Assessing Evidence With Bayesian Statistics Building an index of evidence is a standard operating procedure that can be challenging when the expected empirical observations include such murky and heterogenous material as laws, statistics, technical reports, interviews, etc. At this stage, the data collection and interpretation is empirically counterfactual, which means the probatory value of an evidence is gauged in the light of its certainty and its uniqueness. Thus we wonder how probable it is to find evidence if our hypothesis stands and how probable it is to find the same evidence if it is false. This logic of process tracing can be formalized in Bayesian terms as below. The confirming or disconfirming value of the expected empirical observations depends on their degree of certainty—the probability to find the evidence e, given h: p ( e|h ) —and their uniqueness—the probability to find the evidence e, given ¬h: p ( e|¬h ) . The combination of certainty and uniqueness defines four types of empirical tests, coined “straw-in-the-­ wind”, “smoking gun”, “hoop” and “doubly-decisive” in the political science literature (Van Evera 1997). A straw-in-the-wind test is neither certain nor unique; a doubly-decisive test is both certain and unique; a smoking-gun test is not certain but unique; and a hoop test is certain but not unique. Table 3.3 presents a typology of these four tests. A parsimonious way to assess formally this probatory value is to calculate the posterior confidence given the collected evidence p ( h|e ) with

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Table 3.3  A typology of conventional tests Certainty = p ( e|h )

Uniqueness = p ( e|¬h )

− +

+



Doubly decisive Hoop

Smoking gun Straw in the wind

Source: Elaborated by the authors, based on Collier (2011)

Bayes likelihood theorem (Bennett 2010, 2015). Our prior confidence p ( h ) depends on the previous knowledge supporting h, which can rely on an experiment, a formal model based on a standard linear regression, the results of former empirical tests or even a subjective perception measured by opinion surveys. In absence of this bottom line, a random value of the prior confidence might be that of a flipping coin  p ( h ) = 0.5 . The posterior confidence can then be calculated as follows: p ( h|e ) =

p ( h ) p ( e|h )

p ( h ) p ( e|h ) + p ( ¬h ) p ( e|¬h )

after a positive test;

and p ( h|¬e ) =

p ( h ) p ( ¬e|h )

p ( h ) p ( ¬e|h ) + p ( ¬h ) p ( ¬e|¬h )

after a negative test;

where h is the hypothesis, e is the evidence, ¬h is the alternate hypothesis and ¬e is the absence of evidence (adapted from Bennett 2015). Table 3.4 presents the results of positive and negative tests in bold letter, based on p ( h ) = 0.5 . The random values chosen here for p ( h|e ) and p ( e|¬h ) are consistent with the scales of confirming and disconfirming values of each kind of test. A confirming test means that p ( h|e ) > p ( h ) and a disconfirming test means that p ( h|¬e ) < p ( h ) so the values can neither produce a negative result if the test is positive nor a positive result if the test is negative. Further, a positive result on a straw-in-the-wind test cannot increase the prior confidence in a way that is superior to a positive result on any other test. Conversely, a positive doubly-decisive test cannot increase the prior

0.50 0.50 0.50 0.50

p (h)

Source: Elaborated by the authors

Straw in the wind Hoop Smoking gun Doubly decisive

Tests

0.50 0.50 0.50 0.50

p ( ¬h ) 0.40 0.90 0.40 0.90

p ( e|h ) 0.60 0.10 0.60 0.10

p ( ¬e|h )

Table 3.4  Bayesian formalization of conventional tests

0.30 0.30 0.10 0.10

p ( e|¬h ) 0.70 0.70 0.90 0.90

p ( ¬e|¬h ) 0.57 0.75 0.80 0.90

p ( h|e ) 0.46 0.13 0.40 0.10

p ( h|¬e )

C2 = p ( h|¬e ) − p ( h ) −0.04 −0.38 −0.10 −0.40

C1 = p ( h|e ) − p ( h ) 0.07 0.25 0.30 0.40

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confidence in a way that is inferior to any other test. Eventually the probability of certainty p ( e|h ) is higher in a smoking-gun test than in a hoop test, and the probability of uniqueness p ( e|¬h ) is lower in a hoop test than in a smoking-gun test. Based on these values, straw-in-the-wind tests exhibit the lowest confirming (0.07) and disconfirming (−0.04) values. Conversely, doubly-decisive tests show the highest confirming (0.4) and disconfirming (−0.4) values. At an intermediate level, hoop-tests show a lower confirming value than smoking-gun tests (0.25 vs 0.3) but a higher disconfirming value (−0.38 vs −0.1). In the policy design framework, instruments of nodality, authority, treasure and organization should be treated as hoop tests, even if some of them may be treated as doubly decisive.3 The rationale here is that if a policy exists there is a high probability to find traces of it in these instruments (so p ( e|h ) = 0.9 ), but there is still a high probability to find these fingerprints in absence of such a policy, (so p ( e|¬h ) = 0.3 ). For instance, if a nationalist oil policy exists, there is a high probability to find traces of nationalism features in the oil policy mix combining instruments of nodality, authority, treasure and organization. Yet finding traces of resource nationalism attributes in one of those instruments does not mean this policy is nationalist. This conservative strategy seeks to avoid the potential statistical bias due to tests sequencing (for instance performing a hoop test before or after a doubly decisive would affect the final result of the tests series). It also spares the tedious exercise of assessing certainty and uniqueness through random values selection (Paz and Fontaine 2018). Based on these values, the replication of four independent hoop tests on the instruments used in the policy design framework allows to upgrade or downgrade the main hypothesis for each part of the causal process. Table 3.5 displays the results of a simulation of such tests in bold letter, based on p ( h ) = 0.5 and the random values described above. After four hoop tests, the posterior confidence p ( h|e ) varies from 0.99 (with 4/4 positive tests) to 0.79 (with 3/4 positive tests), to 0.16 (with 2/4 positive tests) and to 0.01 (with 1/4 positive test). This means if only 1/4 test was negative or inconclusive the corresponding part of the main hypothesis—hence the overall theoretical process—would remain indeter-

3  For instance treasure instruments could provide doubly decisive tests, since there is a high probability to find a treasure instrument in any policy, and finding a treasure instrument in absence of a policy would be awkward.

Tests result

+ + + + − + + + − − + + − − − +

Empirical tests

PT1 PT2 PT3 PT4 PA1 PA2 PA3 PA4 PB1 PB2 PB3 PB4 PC1 PC2 PC3 PC4

0.50 0.75 0.90 0.96 0.50 0.13 0.30 0.56 0.50 0.13 0.02 0.06 0.50 0.13 0.02 0.00

p (h) 0.50 0.25 0.10 0.04 0.50 0.88 0.70 0.44 0.50 0.88 0.98 0.94 0.50 0.88 0.98 1.00

p ( ¬h ) 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90

p ( e|h ) 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10

p ( ¬e|h )

Table 3.5  Bayesian formalization of 4 × 4 hoop tests series

0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30

p ( e|¬h ) 0.70 0.70 0.70 0.70 0.70 0.70 0.70 0.70 0.70 0.70 0.70 0.70 0.70 0.70 0.70 0.70

p ( ¬e|¬h ) 0.75 0.90 0.96 0.99 0.75 0.30 0.56 0.79 0.75 0.30 0.06 0.16 0.75 0.30 0.06 0.01

p ( h|e ) 0.13 0.30 0.56 0.79 0.13 0.02 0.06 0.16 0.13 0.02 0.00 0.01 0.13 0.02 0.00 0.00

0.25 0.40 0.46 0.49 −0.38 −0.20 0.06 0.29 −0.38 −0.48 −0.44 −0.34 −0.38 −0.48 −0.50 −0.49

p ( h|¬e ) C1 = p ( h|e ) − p ( h )

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minate, and if at least 2/4 tests were negative or inconclusive, the prior confidence should be downgraded. Once the expected empirical observations have been turned into confirming or disconfirming evidence for the theoretical causal process, the research can proceed to cross-case comparison for theory testing. 3.4  Cross-case Comparison Cross-case comparison of causal mechanisms requires answering the following questions: What to compare? Why? How? (Fontaine 2017). “What to compare?” refers to the challenge of moving forward from within-case to cross-case analysis. Considering process tracing is a within-case research method, comparative process tracing may sound like an oxymoron. That being said, a single within-case analysis is of limited interest from a dualist ontology, since it does not allow to go beyond a contingent explanation of a causal process. In other words, be it realist or neo-positivist, causal process tracing reveals its best potential when combined with small-n or largen comparison in a multi-method research design. However, unlike ­ neo-positivists, realists compare causal mechanisms as a whole, not as sets of intervening variables. “Why compare?” is related to the problem of moving forward from theory building to theory testing. Once a theoretical causal mechanism has been empirically validated, any additional case is to be compared to the former for a confirming or a disconfirming purpose. To confirm a causal mechanism in the policy design of a typical case (CS1) requires to compare this case with at least one other typical case (CS2). Yet this cannot be sufficient to draw any conclusion regarding the portability of this mechanism, basically because selecting only cases positive on the cause and the outcome would create a theoretical bias. Further, a theory may turn out to be trivial in absence of any deviant case. Hence the necessity to compare typical cases with at least one deviant case (CS3), that is to say a case positive on the cause but negative on the outcome. This is the only way to explain a mechanism breakout or deviance (in which case the comparison would still be confirming) or to identify any inconsistency in the theorized mechanism (in which case the comparison would be disconfirming by suggesting the existence of omitted conditions or spurious variables). However in realist process tracing the counteracting forces cannot be treated as intervening variables since they constitute causal forces (mechanisms) by themselves.

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“How to compare?” refers to the causal process operationalization and case selection. As already mentioned above, case selection in a multi-­ method research design is neither based on the trigger nor on the outcome, but on the hypothetical relationship between them both (Beach and Rohlfing 2015; Beach and Pedersen 2016). As a consequence, it is neither affected by the dilemma of causes-of-effects versus effects-of-­ causes criteria (Goertz and Mahoney 2012), nor by the problem of statistical bias raised by the selection on the dependent variable (Geddes 2003). Table 3.6 displays a four-case comparison based on the causal mechanism of a policy outcome. The first typical case is expected to provide evidence of the main hypothesis for theory building. Here the adoption of new policy aims triggers the formulation of a new policy, which produces a change in the institutional system, which determines the adoption of a particular implementation style in State-society relationships regarding the new policy, Table 3.6  Cross-case comparison of causal mechanisms Theoretical process

Main hypothesis

Agenda-­ setting (T)

Government aims at economic development through resource nationalism (HT) Typical case + 1 (Venezuela) Typical case + 2 (Ecuador) Deviant + case 1 (Brazil) Deviant + case 2 (Mexico)

Policy formulation (A)

Cross-­ sectorial coordination (B)

Political interplays (C)

Policy outcome (O)

Government formulates a new oil policy based on resource nationalism (HA)

Government adapts the institutional system to support the new oil policy (HB)

Government limits social control and citizens participation in the oil policy (HO)

+

+

Government adopts a hierarchical implementation style to cope with non-State actors contest (HC) +

+

+

+

+

+

+







+







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which produces a policy outcome. The second typical case is expected to provide the same kind of evidence confirming the main hypothesis for theory testing. The deviant cases are expected to provide conclusive evidence of the necessity of each entity engaged in activity to produce the expected outcome (Schneider and Rohlfing 2013). This means in absence of evidence or when evidence of absence were found, the alternate hypothesis would stand for at least one entity of the causal mechanism (¬hA, ¬hB or ¬hC) and consequently for the outcome (¬hO). For instance, given ¬hB (the new policy does not produce an institutional change), we expect to find ¬hC (the government does not favor the expected implementation style) and ¬hO (the government does not account for the expected policy outcome). After comparing these cases the initial main hypothesis might be partly revisited in order to explain the effect of contingency in the policy design. In the example used above, if the negative tests explain the deviation of the mechanism in cross-sectorial coordination (¬hB), this could mean that institutional resilience is stronger than the government’s will or capacity. 3.5  Research Protocol The successive steps described above can eventually be related with their corresponding objectives and modalities in the five-step research protocol presented in Fig. 3.2. These standard operating procedures were applied to compare the causal mechanism linking resource nationalism to public accountability deficits in four oil producing countries: Venezuela, Ecuador, Mexico and Brazil. • Step 1 is the process theorization for theory building or reformulation. It consists in the identification and operationalization of the trigger, the outcome and the causal mechanism in-between, through the formulation of the main research hypothesis and its alternate hypotheses. The theorization is based on previous knowledge gathered through a state of the art or former case studies which inform us about the hypothesized causal process linking the adoption of a policy aim to the production of a policy outcome. • Step 2 is about listing the expected empirical observations if the main hypothesis stands and assessing their probative value based on the typology of empirical tests by their certainty and uniqueness (straw-­ in-­the-wind, hoop, smoking-gun and doubly decisive). Here, the

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Trigger, outcome and causal mechanism Step 1 - Theorization

Theory building / reformulation Main / alternate hypotheses

Policy instruments Step 2 - Empirical tests design

Hoop tests Bayesian formalization

cs-QCA for causal homogeneity Step 3 - Case selection

Typical / Deviant / Irrelevant / Inconsistent fs-QCA for consistency

Step 4 - Congruence analysis

Typical/deviant cases for confirming /disconfirming purpose Cross-case comparison Interpretation and revision

Positive / negative tests results Step 5 - Deep with in-case study

Process tracing Interpretation, discussion, conclusions

Fig. 3.2  Standard operating procedures for comparative policy design. (Source: Elaborated by the authors)

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four kinds of policy instruments by the State’s resources of nodality, authority, treasure and organization are treated as hoop tests for their highly certain but non-unique nature, as formally assessed with the Bayesian theorem of likelihood. The design of these tests is purposely conservative and systematic in order to reach parsimonious but strong conclusions. • Step 3 consists in selecting cases based on the typology of typical, deviant, irrelevant and inconsistent cases. It deals with the causal homogeneity of a case population through crisp-set qualitative comparative analysis (cs-QCA) and external consistency of the selected cases through fuzzy-set qualitative comparative analysis (fs-QCA). The selection can be on either type of cases, as long as it is coherent with the researcher’s purpose of theory building, testing (confirming or disconfirming) or reformulation. • Step 4 deals with the congruence analysis through cross-case comparison. It aims at assessing the positive or negative results of the empirical tests designed in step 3, for each entity of the causal mechanism, plus the trigger and the outcome of the process. The confirming or disconfirming value of these evidence is interpreted and discussed at each stage along the pathway, which allows to revise the initial hypothesis before engaging in a deep within-case study. • Step 5 is deep within-case for theory testing based on process tracing. It aims at confirming or disconfirming the main hypothesis according to the collected evidence. An index of evidence is presented in the research appendix. If a typical or a deviant case confirms the theory built in step 1 the conclusions drawn from the first case in step 4 become stronger. Conversely whenever the results are disconfirming in a typical or a deviant case, the conclusions drawn from the first case are weakened, so they should be revised and a new research design should start up from step 1.

4   A Causal Mechanism of Public Accountability Deficit 4.1  Causal Mechanism Theorization 4.1.1 First Hypothesis: H1 = RN:PA− According to our initial research hypothesis, resource nationalism hinders public accountability when the following mechanism is set in motion. A

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Theorization

Resource nationalism to secure development

New oil policy favors StateControl over FDI

Centralized cross-sectorial coordination

Hierarchical implementation style

Public accountability deficit

Operationalization

government aims at securing development through resource nationalism (hT), which causes the formulation a new oil policy favoring State control over foreign direct investments (FDI) (hA). Consequently the government centralizes the cross-sectorial coordination around the new oil policy (hB), then adopts a hierarchical implementation style to cope with the demands by non-State actors during the policy implementation (hC). This ends up creating a public accountability deficit (hO). This mechanism is based on the theory of the State-led re-assertive policy style, according to which a government favors steering, redistribution and intervention when ­addressing policy problems by the State’s function, by social factors or by political aims (Pierre and Peters 2000, 204). It is operationalized by observing change in policy aims and means, in the institutional system, in Sate-­ society relationships and in public accountability procedures (Cf. Fig. 3.3). Following the Bayesian logic underpinning realist process tracing, any other hypothesis is treated as a single alternate hypothesis for each part of the mechanism. These alternate hypotheses state that the government does not aim at securing development through resource nationalism (¬hT); he does not formulate a new oil policy based on resource nationalism (¬hA); he does not centralize the institutional system to support the new oil policy (¬hB); he does not adopt a hierarchical implementation style to

Change in public policy aims

Change in sectorial policy

Change in institutional system

Change in State-society relationships

Change in public accountability regimes

Fig. 3.3  A simple theoretical causal mechanism of resource nationalism hindering public accountability (H1)

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cope with the demands by non-State actors (¬hC); and social control and participation in the oil policy are not limited (¬hO). However our method is based on the realist rule of necessary causality, according to which the presence of a causal force is necessary for an outcome to be caused by a factor. This requires our comparing counterfactually the typical cases (where RN∗PA−) with deviant cases where resource nationalism does not come along with a public accountability deficit (RN∗¬PA−), inconsistent cases where a public accountability deficit is observed in absence of resource nationalism (¬RN∗PA−) and individually irrelevant cases where neither resource nationalism nor a public accountability deficit is observed (¬RN∗¬PA−). The individually irrelevant case is the easiest one to deal with, since process tracing is about explaining the necessary (deterministic) causal mechanism linking T and O, not a symmetrical (probabilistic) causation: the alternate hypothesis to T:O (a trigger is responsible for an outcome) is not ¬T:¬O (the absence of a trigger is responsible for the absence of an outcome). The inconsistent case might raise serious concerns regarding our main hypothesis, since a method of within-case or small-n comparison does not allow to address equifinality due to the degree of freedom problem (more variables to control for than selected cases for comparison). Then again, realist process tracing does not deal with the many possible causes of an outcome (in the present case, a public accountability deficit) but with the causal force that makes one particular factor (here, resource nationalism) trigger the process leading to this outcome. The deviant case is the most important one for theory-testing as it raises the tricky problem of context in process tracing. If our main hypothesis (H1) stands in a typical case—the adoption of a policy agenda based on resource nationalism (T) is a sufficient cause of public accountability deficit (O)—then there is a causal mechanism in between, each part of which is an insufficient but necessary entity (A, B, C) engaged in an activity consistent with the others, so that a trigger causes an outcome (T:O). If it stands in a deviant case, it means a contextual factor is at work, that makes the mechanism deviate or break out in A, B or C, so that the trigger leads to another outcome (T:¬O). So what could possibly counter the negative effect of resource nationalism on public accountability? Solving this riddle requires wondering what may happen in each entity (A, B and C) of the causal mechanism. According to H1, hA = T:A, which means resource nationalism has the government adopting a nationalist oil policy. In that case, the government actually

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intents to do what he says and the ideas contained in the policy agenda (Id) are turned into a new oil policy (P), so that Id:∆P. On the contrary if hA does not stand—a nationalist oil policy is not formulated, in spite of the resource nationalist aims adopted by a government—then A is inconsistent with T. This means the oil policy remains unchanged or, if it changes, it does not pursue the objectives put on the agenda. Then this case becomes one of non-design (Peters 2018, 19), whose study would be of little interest to disentangle the causal mechanism of a policy outcome. At best, such a case would be of interest if we were to explain an ­implementation gap (why a government says something and does nothing or acts opposite to his word), which would be a different causal mechanism of T:¬A. Things are different for the remaining entities, regardless whether the expected outcome happens or not. According to H1, the government coordinates the new oil policy with other related policy areas in a hierarchical way (hB = A:B), so that this policy subordinates or subsumes other substantive policy areas. This means the new oil policy (P) causes a change in existing institutions (P:∆In). If hB does not stand then the new oil policy is not hierarchically coordinated with other related policy areas, which means existing institutions are constraining for the new oil policy (In:∆P). Further, in H1 the hierarchical policy coordination leads the government to coerce State-society relationships regarding the new oil policy (hC = B:C). This means the government is ready to implement the new policy even against non-State actors’ will and P affects existing adverse interests (P:∆It). If hC does not stand then the government does not manage the relationships with non-State actor in a coercive way. Hence P is affected by adverse interests (It:∆P). According to our main hypothesis, the fate of the new oil policy depends on whether the implementation style is centralist or not in B, and whether it is hierarchical or not in C. On one hand, the case where the mechanism deviates in B is of utmost interest insofar as it sheds light on the relationship between ideas (Id) and institutions (In) in a policy design: whether institutions are constraining for new ideas or not is key to explain a policy outcome. On the other hand, if the mechanism deviates in C, the case may shed light on the relationship between institutions and interests (It) in policy design: whether interests are constraining or not is also key to explain a policy outcome. That being said, B:¬C is unlikely because if hB stands (cross-sectorial coordination is centralized) the government should be able to manage hierarchically the political interplays about the new policy, even against the

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explicit opposition by non-State actors. Likewise, C:¬O is unlikely because if hC stands (the government favors coercion in State-society relationships) there is no reason the same government would care much for public accountability. Consequently, the causal mechanism of a policy outcome is most likely to deviate or break out in B (A:¬B). Either way the comparison of deviant cases with typical ones aims at clarifying the main hypothesis by putting it into context. We can now turn our attention towards contextual factors that might explain when resource nationalism is not a sufficient cause for a deficit of public accountability. 4.1.2 Coping With Context: H2 = RN∗¬Tr:PA− Whatever the alternate hypothesis regarding A (¬A = A′), we just saw that if A′ meant “the oil policy is not nationalist”, it would be inconsistent with T and the case would become a case of non-design. But if A′ meant “another policy is constraining for resource nationalism”, then A′ might be consistent with T and explain the alternate hypothesis in B (¬B = B′). If hB′ stands, so that a non-nationalist policy counters the new oil policy in cross-sectorial coordination, then B′ is consistent with A′. So our main hypothesis may be reformulated as follows: the combination of a nationalist oil policy with another policy produces a non-centralized cross-sectorial coordination (A∗A′:B′). This means the deviant point of our causal mechanism is to be found in B. If it was not the case, there would be an inconsistency between A′—another policy is constraining for resource nationalism—and B′—the new oil policy is not constraining for other policy areas. Not every policy can actually counter the negative effects of resource nationalism on public accountability without entering into contradiction with it. But the transparency policy is one that has been clearly identified and most studied recently in the literature on democratic governance (Riddell 2013; Calland and Bentley 2013; Carlitz 2013), especially regarding the extractive sector (Gillies 2010; Haufler 2010; Mejía Acosta 2013; Öge 2016). Even if the causal mechanism linking them remains a controversial issue (Hood and Heald 2006; Fox 2007; López Ayllón 2007; Mabillard and Zumofen 2016), there is hardly any doubt that transparency is a necessary but not sufficient condition to improve public accountability. Therefore, could it be that the causal mechanism linking resource nationalism with a public accountability deficit deviates when a government simultaneously implements a nationalist oil policy and a transparency

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policy? In that case, if hA′ stands—a transparency policy is formulated by a government—then A′ is consistent with T and B′ (so that T:A∗A′:B′). This means the coordination of a nationalist oil policy with a transparency policy could explain why existing institutions constrain the new policy (In:∆P). Conversely, if the new oil policy was coordinated with another policy that is not nationalist but produces the same result in B (so that A∗A′:B) then the other policy would be irrelevant to explain the mechanism’s deviance between T and ¬O. Once rephrased, our hypothesis is twofold as showed in Fig. 3.4. The government adopts new policy aims that feature resource nationalism, setting a nationalist policy agenda. In this sense, it explicitly endorses an expansion of the government take from the oil and gas industry (rent-­ seeking), to foster State-driven development and oil-rents spillovers (hT). Once this trigger is set into motion, the government proceeds to formulate a nationalist oil policy (hA) focused on ensuring the national sovereignty, strengthening the State’s power and control over the petroleum sector, and improving the capacity of the national oil company. Then the government adapts the institutional system to support the new oil policy through cross-sectorial coordination. In absence of a transparency policy, the new oil policy is unambiguously placed in a central position (hB).

Closed nationalism

Centralized cross-sectorial coordination

Coercive implementation style

Public accountability deficit

Opened nationalism

Adaptive cross-sectorial coordination

Participative implementation style

Normal public accountability

Resource nationalism to secure development

Fig. 3.4  A twofold theoretical causal mechanism of resource nationalism hindering public accountability (H2)

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Conversely when a government has adopted a transparency policy the new oil policy is constrained by other policy areas and therefore it is adjusted to existing institutions (hB′). In order to cope with non-State actors’ contest about the new policy, in the first case the government adopts a hierarchical implementation style (hC), in the second case he adopts a participative implementation style (hC′). Eventually the adoption of resource nationalism in absence of a transparency policy creates limitations to social control and citizens’ participation in the oil policy (hO) but the combination of resource nationalism with a transparency policy does not affect public accountability (hO′). 4.1.3 Empirical Tests Design Table 3.7 presents a typology of the expected empirical observations for each part of the causal process of policy design, if our main hypothesis stands. It was built in alignment with the realist policy design methodology presented above (Sect. 2), based on the taxonomy of policy instruments by the State resources of nodality, authority, treasure and organization. These instruments are treated as independent hoop tests (highly certain but non-unique), so that the combination of positive results would upgrade the confidence in our hypothesis in a degree similar to a doubly decisive test, and in the case of more than one negative result the hypothesis should be revised. If hT stands, explicit claims of the government aiming at securing development through resource nationalism should be observed in the government’s program (PT1), in the constitutive regulation (PT2), in the development model (PT3) and in the design of the State apparatus (PT4). If hA stands, a change in the oil policy based on resource nationalism should be seen at a sectorial level in planning (PA1), regulation (PA2), budget allocation (PA3) and administration (PA4). If hB stands, a change in the institutional system aimed at supporting the new policy should be observed at a cross-sectorial level in planning (PB1), regulation (PB2), budget allocation (PB3) and administration (PB4). If hC stands, a hierarchical implementation style to cope with non-State actors contest should be observed in the government’s statements (PC1), in the legislative process (PC2), in the State’s budget elaboration (PC3) and in local governments’ role in the oil policy (PC4).

Government aims at economic development through resource nationalism (hT) Explicit claims in the government’s program (PT1) Explicit claims by government in the constitutive regulation (PT2) Explicit claims by government in the development model (PT3) Explicit claims by government in the State apparatus design (PT4)

Source: Elaborated by the authors

Organization instruments

Treasure instruments

Authority instruments

Nodality instruments

Hypothesis

Change in the policy area administration (PA4)

Change in the policy area budget allocation (PA3)

Change in the policy area regulation (PA2)

Government formulates a new oil policy based on resource nationalism (hA) Change in the policy area planning (PA1)

Government adopts a hierarchical implementation style to cope with contest by non-State actors (hC) Traces in the government’s statements (PC1) Traces in the legislative process (PC2)

Change in the cross-sectorial administration (PB4)

Traces in the local governments role in oil policy (PC4)

Change in the Traces in the budget cross-sectorial budget elaboration (PC3) allocation (PB3)

Change in the cross-sectorial planning (PB1) Change in the cross-sectorial regulation (PB2)

Government adapts the institutional system to support the new oil policy (hB)

Table 3.7  Expected empirical observations in a policy design process

Limited autonomy by balance and control agencies (PO4)

Limited financial assessments by the government (PO3)

Limited access to the information system (PO1) Limited respect of the due process by State agencies (PO2)

Government limits citizens participation and social control in the oil policy (hO)

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Eventually if hO stands, a public account of the policy outcome limiting citizens participation and social control in the oil policy should appear through limitations in the access to the information system (PO1), in the respect of the due process by State agencies (PO2), in the delivery of timely financial assessments by the government (PO3) and in the autonomy of balance and control agencies (PO4). Once our main hypothesis has been clarified by taking into consideration contextual elements that could explain the existence of deviant cases, we can proceed with the case selection for comparison, based on the theoretical mechanism described above. 4.2  Case Selection 4.2.1 Overall Cases Population The total population of cases includes nine oil and gas producing countries in Latin America and the Caribbean (LAC). Based on the latest reform in the petroleum sector made by governments until 2017, these countries can be gathered in two conventional groups: nationalist and liberal. A nationalist oil policy refers to the situation where a government favors State-driven development, as opposed to market-driven development pursued through liberal policies (Weintraub et al. 2007). The latest nationalist reforms were implemented chronologically in five countries: Venezuela, Bolivia, Brazil, Ecuador and Argentina. In Venezuela the government of Hugo Chavez (1999–2013) implemented a structural reform in the petroleum sector through the creation of mixed companies with PdVSA (Petróleos de Venezuela S.A.), in 2000. In Bolivia the government of Evo Morales (2006–2018) nationalized the country’s gas sector in 2006. At the same time in Brazil Ignacio da Silva Lula’s administration (2003–2010) nationalized the “Lula oil field” located in the pre-salt reservoir off-shore, which is the country’s main project operated by Petrobras (Petróleo Brasileiro S.A.). Later on, in Ecuador, Rafael Correa’s administration (2007–2016) canceled all existing contracts with multinational companies in 2010, which were then forced to sign up service contracts with Petroecuador (Petróleos del Ecuador). Eventually in Argentina the government of Cristina Kirchner (2007–2015) nationalized Repsol-YPF in 2012, thus recasting YPF (Yacimientos Petrolíferos Fiscales) which had been privatized during the 1990s.

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Liberal reforms were implemented in four countries: Trinidad and Tobago, Peru, Colombia and Mexico. In Trinidad and Tobago the Noor Hassanali’s administration (1987–1997) completed the reform of the national company Petrotrin (Petroleum Company of Trinidad and Tobago), which did not alter the market-driven orientation stated by the 1969 Petroleum Act but helped expanding natural gas sector. In Peru the government of Alejandro Toledo (2001–2006) launched the bids for the Camisea project following up former President Alberto Fujimori’s neo-­ liberal gas policy. In Colombia the government of Juan Manuel Santos (2010–2018) pursued the privatization of the petroleum sector initiated by former President Alvaro Uribe. In Mexico Enrique Peña Nieto’s administration (2012–2018) opened the upstream to the private sector in 2013 thus putting an end to the State monopoly by Pemex (Petróleos de México S.A.), thus concluding a process launched by former President Felipe Calderon. 4.2.2 Assessing Resource Nationalism Based on the definition of resource nationalism as a regime of natural resources governance (Mares 2010; Haslam and Heidrich 2016a, b), the attributes of T—a government claims explicit nationalist aims for development—are threefold: a government expects oil rents spillover for a country’s development (X1), he seeks to increase oil rents through the contractual regime (X2) and he seeks to control the oil sector through a national oil company (NOC) (X3). These attributes are generally taken into consideration in the literature on energy governance and oil and gas policy, so they can be easily tracked in secondary sources such as the US Energy Information Agency (EIA) reports, the Inter-American Development Bank (IDB) policy papers and reports on energy governance, and companies’ institutional websites. A way to assess X1 is to see if a NOC’s investment capacity depends on the government’s will and is prior or posterior to public spending planning. This materializes in the Ministry of Finance and the Ministry of Energy sitting on the company’s board to transmit the government’s priorities. In a nationalist regime, the NOC’s investments are defined by the State’s budget after gross benefits have been included in the overall State’s incomes. In a liberal regime, the NOC enjoys more autonomy since its investments are planned before benefits being transferred to the State. Therefore in the former case the NOC’s investment capacity depends on

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the annual Law on Finance, in the later case it depends on the company’s annual operational plan. To assess X2 one can see if the government favors service contracts as opposed to production sharing agreements. The difference between these contractual regimes lays in the way the government-take is calculated. In both cases it depends on the risk factor (R) defined by the volume, the quality and the accessibility of oil and gas reserves. But in a production sharing agreement the private partner can subtract her operational spendings from the gross profit before sharing benefits with the State, which affects negatively the government-take. Conversely in a service contract the government-take is established before the private partner subtracts her operational spendings, which guarantees a higher rent and forces the private corporation to be more productive. The election of one kind of contractual regime or another implies a trade-off between attracting FDI and protecting the national sovereignty. At a constant volume of production, a nationalist government would rather trade FDI for more sovereignty in order to increase oil rents, but a liberal government would rather trade sovereignty for FDI in order to increase the country’s production capacity and proven reserves. A way to assess X3 is to see if the NOC is granted a special status with exclusivity or pre-emptive rights in operations engaging private corporations. This gives leverage to a nationalist government to control the petroleum sector and to guarantee the State’s participation in upstream and downstream operations. Conversely a liberal government would rather have the NOC competing in equal conditions with private corporations, because it is key to improve corporate governance. 4.2.3 Assessing Transparency Policies Since the first report by the Berlin based NGO Transparency International, in 1993, transparency has become compulsory in democratic countries. Yet it refers to a wide variety of government’s attitudes, ranging from voluntary to mandatory disclosure, and uncovers many different aspects of public policies, including the most traditional fundamental rights, like the freedom of the press, or more innovative instruments, such as participatory budgeting (Porto 2017). The diffusion of freedom of information laws around the world (Michener 2011) has also contributed to this conceptual stretching, which makes it difficult to define clear-cut class membership of governments adopting transparency policies or not.

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One thing is for sure, the diffusion of these policies around the world would not have been possible without the multiplication of international programs supported by bilateral and international organizations. From the Open Government Partnership (OGP) launched by former British Prime Minister Tony Blair in 2000 (Bowles et al. 2013) to the Extractive Industries Transparency Initiative (EITI) launched in 2002 under the World Bank’s patronage (Haufler 2010), these programs have offered new opportunities for citizens to advocate for more accountable institutions and policies. Local communities, trade unions, NGO and other organizations from the civil society use international fora as a soundbox for their claims, in order to exert pressure on local authorities and have the regulation reformed following the boomerang theory (Keck and Sikkink 1998). While the adoption of a law on transparency may cover significant differences from one country to another, the ratification of international commitments through these programs is a good indication of a government’s will to promote transparency through a specific policy agenda. The OGP and the EITI are consistent with this premise, for their long-­standing existence and sectorial relevance. Both programs have different objectives regarding transparency and they are managed by distinct organizations, which make them statistically non-redundant. Therefore the attributes of Tr—a government formulates a transparency policy—can be a country’s compliance with the OGP (W1) or the EITI (W2). Conversely, the fact that a country denies joining both of these programs is a is a good indication of its rulers’ lack of will to foster transparency policy. 4.2.4 Assessing a Public Accountability Deficit Based on the definition of public accountability as a key element of the democratic governance (Mainwaring 2003; Dowdle 2006; Bovens et al. 2014), the attributes of O—there is a deficit of public accountability in the oil and gas policy—are threefold: the society exerts a limited control over the executive (Y1), there is a lack of quality in regulation (Y2) and the rule of law is flawed (Y3). Assessing these attributes would not be possible without an in-depth analysis for each case, which is obviously out of the scope of a case selection process. An alternative solution to this problem is to consider non-State actors’ perceptions of key indicators, such as the Worldwide Governance Indicators (WGI) project (WGI 2019). These indicators provide sufficiently trustworthy data based on pooled time-series built on regular surveys (Kaufmann et al. 2010), to ensure a reasoned case selection, even though perception indicators are just a proxy

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based on subjective expressions by panels of experts and focus groups (Erkkila et al. 2016). The rationale here is that if public accountability is hindered one can expect citizens and corporate actors to complain about the government, the existing regulation and the effectiveness of the law. Conversely one can assume there is probably less or no deficit of public accountability if they express a favorable opinion indicating they are satisfied with their institutions and government’s practices. A good way to assess Y1 is to observe variations in the perception of the overall political and administrative system by non-State actors, which is the “voice and accountability” measured by the WGI project. To assess Y2 one can observe the evolution of non-State actors’ perception of the efficiency of a country’s regulatory system, as measured by “Regulatory quality”. Y3 can be assessed through the evolution of non-State actors’ perceptions of the “Rule of law”, which adds more precision to Y1 and Y2 regarding the efficiency of the regulatory system. 4.3   Results and Discussion The results of the empirical tests on the attributes of T, Tr and O were compiled in a truth table for causal homogeneity, which is presented in Appendix A.  A synthesis of the results is presented in Table  3.8 below. Based on the truth table, all cases were dispatched in a 2 × 2 typology, which is presented in Table 3.8. 4.3.1 Assessing Class Membership for the Trigger (T) Class membership for the trigger (T) is defined by the combination of X (a government adopted resource nationalism) and W (a government adopted a transparency policy). X indicates a government adopted the resource nationalism principles described above. To assess X1, X2 and X3, we used qualitative information on local regulation (hydrocarbon laws, NOC statutes and political constitutions) presented in the EIA’s country profiles (EIA 2018) and the IDB’s policy briefs (IDB 2018). A true positive on X1 means the NOC’s investment capacity depends on the government’s objectives rather than on corporate governance priorities. A true positive on X2 means the government favors service contracts over production sharing agreements. A positive test on X3 means the NOC is granted a special status compared to private corporations, either in upstream or in downstream operations. The combination of the attributes of X (X1∗X2∗X3) indicates a positive result on T (coded 1) in six countries: Argentina,

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Table 3.8  cs-QCA for causal homogeneity Case Argentina under Kirchner (2007–2015) Bolivia under Morales (2006–2018) Brazil under Lula (2003–2010) Colombia under Santos (2010–2018) Ecuador under Correa (2007–2016) Mexico under Peña Nieto (2012–2018) Peru under Toledo (2001–2006) Trinidad and Tobago under Hassanali (1987–1997) Venezuela under Chavez (1999–2013)

X

W

X − W

Y

1.00 1.00 1.00 0.00 1.00 1.00 0.00 0.00 1.00

0.50 0.00 0.50 1.00 0.00 1.00 1.00 1.00 0.00

0.50 1.00 0.50 −1.00 1.00 0.00 −1.00 −1.00 1.00

0.66 1.00 0.33 0.66 1.00 0.33 0.33 0.33 1.00

Source: Elaborated by the authors, based on EIA (2018), WGI (2019), OGP (2018), EITI (2018) X = (X1 + X2 + X3)/2; W = (W1 + W2)/2; Y = (Y1 + Y2 + Y3)/3 X1  =  NOC’s is dependent from government; X2  =  Service contracts favored over Production sharing contracts; X3 = NOC is granted a special status; W1 = Country joined OGP during or after the new policy was formulated; W2 = Country joined EITI during or after the new policy was formulated; Y1 = WGI Voice and accountability variation; Y2  =  WGI Regulatory quality variation; Y3  =  WGI Rule of law variation

Bolivia, Brazil, Ecuador, Mexico and Venezuela. The absence of at least one attribute (¬X1 + ¬X2 + ¬X3) indicates a negative result on T (coded 0) in three countries: Colombia, Peru, and Trinidad and Tobago. These results confirm there is a clear-cut separation between State-driven and market-driven reforms in the petroleum sector. W indicates there is a transparency policy in a country (Tr). To assess W1 and W2 we considered historical information about the OGP and EITI partners, available on the organizations’ websites (OGP 2018; EITI 2018). A true positive test on W1 means a country had joined the OGP program until 2017 (which ends the period of reference for this research). A true positive on W2 means it had joined the EITI likewise. The presence of one of those attributes (W1 + W2) indicates a positive result (coded 1 if the result ≥0.5) in six countries: Argentina, Brazil, Colombia, Mexico, Peru and Trinidad and Tobago. The absence of both attributes (¬W1∗¬W2) indicates a negative test on W (coded 0 if the result